Merge branch 'main' of github.com:HPCL-EI/RoboWaiter
This commit is contained in:
ChenXL97
commit
4feb75e80d
|
|
@ -1,15 +1,20 @@
|
|||
antlr4-python3-runtime
|
||||
py_trees
|
||||
shortuuid
|
||||
shortuuid~=1.0.11
|
||||
protobuf==3.20.0
|
||||
gym==0.21.0
|
||||
grpcio==1.53.0
|
||||
requests
|
||||
urllib3
|
||||
tabulate
|
||||
requests~=2.31.0
|
||||
urllib3~=2.0.7
|
||||
tabulate~=0.9.0
|
||||
autopep8
|
||||
pytorch==1.11.0
|
||||
torchvision==0.12.0
|
||||
torchaudio==0.11.0
|
||||
cudatoolkit=11.3
|
||||
loguru
|
||||
loguru~=0.5.3
|
||||
matplotlib~=3.8.0
|
||||
numpy~=1.26.0
|
||||
setuptools~=68.0.0
|
||||
pydot~=1.4.2
|
||||
colorama~=0.4.6
|
||||
|
|
@ -1,4 +1,5 @@
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import time
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||||
import math
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||||
import grpc
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||||
import numpy as np
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||||
|
||||
|
|
@ -358,29 +359,29 @@ class Scene:
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temp = stub.GetIKControlInfos(GrabSim_pb2.HandPostureInfos(scene=self.sceneID, handPostureObjects=HandPostureObject))
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# 移动到进行操作任务的指定地点
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def move_task_area(self,op_type):
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if op_type==11 or op_type==12: # 开关窗帘不需要移动
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return
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scene = stub.Observe(GrabSim_pb2.SceneID(value=self.sceneID))
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walk_value = [scene.location.X, scene.location.Y, scene.rotation.Yaw]
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if op_type < 8:
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v_list = self.op_v_list[op_type]
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if op_type>=8 and op_type<=10: # 控灯
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v_list = self.op_v_list[6]
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if op_type in [13,14,15]: # 空调
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v_list = [[240, -140.0]] # KongTiao [300.5, -140.0] # 250
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print("------------------move_task_area----------------------")
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print("Current Position:", walk_value,"开始任务:",self.op_dialog[op_type])
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for walk_v in v_list:
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walk_v = walk_v + [scene.rotation.Yaw, 180, 0]
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walk_v[2] = 0 if (op_type in [13,14,15]) else scene.rotation.Yaw # 空调操作朝向墙面
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action = GrabSim_pb2.Action(
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scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.WalkTo, values=walk_v
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)
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scene = stub.Do(action)
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print("After Walk Position:",[scene.location.X, scene.location.Y, scene.rotation.Yaw])
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# def move_task_area(self,op_type):
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# if op_type==11 or op_type==12: # 开关窗帘不需要移动
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# return
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# scene = stub.Observe(GrabSim_pb2.SceneID(value=self.sceneID))
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# walk_value = [scene.location.X, scene.location.Y, scene.rotation.Yaw]
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#
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# if op_type < 8:
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# v_list = self.op_v_list[op_type]
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# if op_type>=8 and op_type<=10: # 控灯
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# v_list = self.op_v_list[6]
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# if op_type in [13,14,15]: # 空调
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# v_list = [[240, -140.0]] # KongTiao [300.5, -140.0] # 250
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# print("------------------error version----------------------")
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# print("------------------move_task_area----------------------")
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# print("Current Position:", walk_value,"开始任务:",self.op_dialog[op_type])
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# for walk_v in v_list:
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# walk_v = walk_v + [scene.rotation.Yaw, 180, 0]
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# walk_v[2] = 0 if (op_type in [13,14,15]) else scene.rotation.Yaw # 空调操作朝向墙面
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# action = GrabSim_pb2.Action(
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# scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.WalkTo, values=walk_v
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# )
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# scene = stub.Do(action)
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# print("After Walk Position:",[scene.location.X, scene.location.Y, scene.rotation.Yaw])
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# 相应的行动，由主办方封装
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def control_robot_action(self, type=0, action=0, message="你好"):
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|
|
@ -512,3 +513,4 @@ class Scene:
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print(scene.info)
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|
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|
|
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|
|
@ -1,59 +0,0 @@
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# !/usr/bin/env python3
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# -*- encoding: utf-8 -*-
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|
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|
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import matplotlib.pyplot as plt
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import numpy as np
|
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import pickle
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import os
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||||
|
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|
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|
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|
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|
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def draw_grid_map(grid_map):
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# 生成新的地图图像
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plt.imshow(grid_map, cmap='binary', alpha=0.5, origin='lower') # 黑白网格
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||||
|
||||
# 绘制坐标轴
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plt.xlabel('y', loc='right')
|
||||
plt.ylabel('x', loc='top')
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||||
|
||||
# 显示网格线
|
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plt.grid(color='black', linestyle='-', linewidth=0.5)
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||||
|
||||
# 显示图像
|
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plt.show()
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||||
#plt.pause(0.01)
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|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
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# control.init_world(scene_num=1, mapID=3)
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# scene = control.Scene(sceneID=0)
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#
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# X = int(950/5) # 采点数量
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# Y = int(1850/5)
|
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# map = np.zeros((X, Y))
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#
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# for x in range(X):
|
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# for y in range(Y):
|
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# if not scene.reachable_check(x*5-350, y*5-400, Yaw=0):
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# map[x, y] = 1
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# print(x, y)
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#
|
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#
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# file_name = 'map_5.pkl'
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# if not os.path.exists(file_name):
|
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# open(file_name, 'w').close()
|
||||
# with open(file_name, 'wb') as file:
|
||||
# pickle.dump(map, file)
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# print('保存成功')
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||||
|
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|
||||
file_name = 'map_5.pkl'
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
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||||
draw_grid_map(map)
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||||
|
|
@ -1,158 +0,0 @@
|
|||
#!/usr/bin/env python3
|
||||
# -*- encoding: utf-8 -*-
|
||||
import math
|
||||
import sys
|
||||
import time
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
from mpl_toolkits.axes_grid1 import make_axes_locatable
|
||||
# from scene import control
|
||||
|
||||
# from rrt import RRT
|
||||
# from rrt_star import RRTStar
|
||||
# from apf import APF
|
||||
from robowaiter.algos.navigate.dstar_lite import DStarLite, euclidean_distance
|
||||
|
||||
class Navigator:
|
||||
'''
|
||||
导航类
|
||||
'''
|
||||
|
||||
def __init__(self, scene, area_range, map, scale_ratio=5, step_length=150, velocity=150, react_radius=300):
|
||||
self.scene = scene
|
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self.area_range = area_range # 地图实际坐标范围 xmin, xmax, ymin, ymax
|
||||
self.map = map # 缩放并离散化的地图 array(X,Y)
|
||||
self.scale_ratio = scale_ratio # 地图缩放率
|
||||
self.step_length = step_length # 步长(单次移动)
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||||
self.step_num = self.step_length // self.scale_ratio # 单次移动地图格数
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||||
self.v = velocity # 速度
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self.react_radius = react_radius # robot反应半径
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||||
|
||||
# self.planner = RRTStar(rand_area=area_range, map=map, scale_ratio=scale_ratio, max_iter=400, search_until_max_iter=True)
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self.planner = DStarLite(area_range=area_range, map=map, scale_ratio=scale_ratio)
|
||||
|
||||
@staticmethod
|
||||
def is_reached(pos: (float, float), goal: (float, float), dis_limit=30):
|
||||
'''
|
||||
判断是否到达目标
|
||||
'''
|
||||
dis = math.hypot(pos[0]-goal[0], pos[1]-goal[1])
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# dis = np.linalg.norm(pos - goal)
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return dis < dis_limit
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|
||||
@staticmethod
|
||||
def get_yaw(pos: (float, float), goal: (float, float)):
|
||||
'''
|
||||
得到移动方向
|
||||
'''
|
||||
return math.degrees(math.atan2((goal[1] - pos[1]), (goal[0] - pos[0])))
|
||||
|
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def legalize_goal(self, goal: (float, float)):
|
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'''
|
||||
TODO: 处理非法目标
|
||||
目标在障碍物上：从目标开始方形向外扩展，直到找到可行点
|
||||
目标在地图外面：起点和目标连线最靠近目标的可行点
|
||||
'''
|
||||
return goal
|
||||
|
||||
def navigate(self, goal: (float, float), animation=True):
|
||||
'''
|
||||
单次导航，直到到达目标
|
||||
'''
|
||||
if not self.scene.reachable_check(goal[0], goal[1], 0):
|
||||
goal = self.legalize_goal(goal)
|
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|
||||
pos = (self.scene.status.location.X, self.scene.status.location.Y) # 机器人当前: 位置 和 朝向
|
||||
print('------------------navigation_start----------------------')
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while not self.is_reached(pos, goal):
|
||||
dyna_obs = [(walker.pose.X, walker.pose.Y) for walker in self.scene.status.walkers] # 动态障碍物(顾客)位置列表
|
||||
dyna_obs = [obs for obs in dyna_obs if euclidean_distance(obs, pos) < self.react_radius] # 过滤观测范围外的dyna_obs
|
||||
# 周围有dyna_obs则步长减半
|
||||
if dyna_obs:
|
||||
step_num = self.step_num // 2
|
||||
else:
|
||||
step_num = self.step_num
|
||||
path = self.planner.planning(pos, goal, dyna_obs)
|
||||
if path:
|
||||
if animation:
|
||||
self.planner.draw_graph(step_num) # 画出搜索路径
|
||||
next_step = min(step_num, len(path))
|
||||
next_pos = path[next_step - 1]
|
||||
# print('plan pos:', next_pos, end=' ')
|
||||
yaw = self.get_yaw(pos, next_pos)
|
||||
# print("yaw:",yaw)
|
||||
self.scene.walk_to(next_pos[0], next_pos[1], Yaw=yaw, velocity=self.v, dis_limit=10)
|
||||
# pos = (self.scene.status.location.X, self.scene.status.location.Y)
|
||||
# if self.is_reached(pos, next_pos):
|
||||
self.planner.path = self.planner.path[next_step - 1:] # 去除已走过的路径
|
||||
pos = (self.scene.status.location.X, self.scene.status.location.Y)
|
||||
# print('reach pos:', pos)
|
||||
|
||||
self.planner.reset() # 完成一轮导航，重置变量
|
||||
|
||||
if self.is_reached(pos, goal):
|
||||
print('The robot has achieved goal !!')
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
# def navigate(self, goal: (float, float), path_smoothing=True, animation=True):
|
||||
# pos = np.array((self.scene.status.location.X, self.scene.status.location.Y)) # 机器人当前: 位置 和 朝向
|
||||
# yaw = self.scene.status.rotation.Yaw
|
||||
# print('------------------navigation_start----------------------')
|
||||
#
|
||||
# path = self.planner.planning(pos, goal, path_smoothing, animation)
|
||||
# if path:
|
||||
# self.planner.draw_graph(final_path=path) # 画出探索过程
|
||||
# for (x, y) in path:
|
||||
# self.scene.walk_to(x, y, yaw, velocity=self.v)
|
||||
# time.sleep(self.step_time)
|
||||
# pos = np.array((self.scene.status.location.X, self.scene.status.location.Y))
|
||||
#
|
||||
# self.planner.reset()
|
||||
#
|
||||
# if self.is_reached(pos, goal):
|
||||
# print('The robot has achieved goal !!')
|
||||
|
||||
'''APF势场法暂不可用'''
|
||||
# while not self.is_reached(pos, goal):
|
||||
# # 1. 路径规划
|
||||
# path = self.planner.planning(pos, goal, path_smoothing, animation)
|
||||
# self.planner.draw_graph(final_path=path) # 画出探索过程
|
||||
#
|
||||
# # 2. 使用APF导航到路径中的每个waypoint
|
||||
# traj = [(pos[0], pos[1])]
|
||||
# #self.planner.draw_graph(final_path=traj) # 画出探索过程
|
||||
# for i, waypoint in enumerate(path[1:]):
|
||||
# print('waypoint [', i, ']:', waypoint)
|
||||
# # if (not self.scene.reachable_check(waypoint[0], waypoint[1], yaw)) and self.map[self.planner.real2map(waypoint[0], waypoint[1])] == 0:
|
||||
# # print('error')
|
||||
# while not self.is_reached(pos, waypoint):
|
||||
# # 2.1 计算next_step
|
||||
# pos = np.array((self.scene.status.location.X, self.scene.status.location.Y))
|
||||
# Pobs = [] # 障碍物(顾客)位置数组
|
||||
# for walker in self.scene.status.walkers:
|
||||
# Pobs.append((walker.pose.X, walker.pose.Y))
|
||||
# next_step, _ = APF(Pi=pos, Pg=waypoint, Pobs=Pobs, step_length=self.step_length)
|
||||
# traj.append((next_step[0], next_step[1]))
|
||||
# #self.planner.draw_graph(final_path=traj) # 画出探索过程
|
||||
# while not self.scene.reachable_check(next_step[0], next_step[1], yaw): # 取中点直到next_step可达
|
||||
# traj.pop()
|
||||
# next_step = (pos + next_step) / 2
|
||||
# traj.append((next_step[0], next_step[1]))
|
||||
# #self.planner.draw_graph(final_path=traj) # 画出探索过程
|
||||
# # 2.2 移动robot
|
||||
# self.scene.walk_to(next_step[0], next_step[1], yaw, velocity=self.v)
|
||||
# # print(self.scene.status.info) # print navigation info
|
||||
# # print(self.scene.status.collision)
|
||||
# time.sleep(self.step_time)
|
||||
# # print(self.scene.status.info) # print navigation info
|
||||
# # print(self.scene.status.collision)
|
||||
# self.planner.reset()
|
||||
|
|
@ -1,52 +0,0 @@
|
|||
## 默认使用RRTStar+路径平滑
|
||||
|
||||
### apf.py: 势场法实现
|
||||
|
||||
### discretize_map.py: 地图离散化并压缩
|
||||
|
||||
### map_5.pkl: 地图文件(5倍压缩)
|
||||
|
||||
### navigate.py: 导航类
|
||||
|
||||
### pathsmoothing.py: 路径平滑
|
||||
|
||||
### rrt.py: RRT实现
|
||||
|
||||
### rrt_star.py: RRTStar 实现
|
||||
|
||||
### test.py: 测试文件
|
||||
|
||||
|
||||
|
||||
|
||||
## TODO
|
||||
|
||||
### 目标不合法
|
||||
#### 初始目标不合法
|
||||
目标在障碍物上：从目标开始方形向外扩展，直到找到可行点
|
||||
目标在地图外面：起点和目标连线最靠近目标的可行点
|
||||
对不合法的目标做单独处理，生成新的目标
|
||||
|
||||
#### 在移动过程中目标被占据
|
||||
给出目标但不会行移动，程序会继续运行，重新计算规划路径，给出新目标
|
||||
|
||||
|
||||
### 规划中断情况
|
||||
|
||||
|
||||
### 计算转向角
|
||||
`完成`
|
||||
|
||||
|
||||
### 有些本来可达的位置却无法走到（系统bug?）
|
||||
例如从初始位置(247, 500) 移动到(115, -10)，无法到达
|
||||
`(已解决)将dis_limit设为小值5而非0`
|
||||
#### 构型空间膨胀？？
|
||||
`不需要`
|
||||
|
||||
### 只考虑一定范围内的行人
|
||||
观测范围 / 反应半径
|
||||
|
||||
`完成`
|
||||
#### 观测范围内有行人步长要减小
|
||||
`完成`
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
|
|
@ -0,0 +1,90 @@
|
|||
# !/usr/bin/env python3
|
||||
# -*- encoding: utf-8 -*-
|
||||
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import pickle
|
||||
import os
|
||||
|
||||
from scipy.ndimage import binary_dilation
|
||||
|
||||
from scene import scene
|
||||
|
||||
|
||||
def draw_grid_map(grid_map):
|
||||
# 生成新的地图图像
|
||||
plt.imshow(grid_map, cmap='binary', alpha=0.5, origin='lower') # 黑白网格
|
||||
|
||||
# 绘制坐标轴
|
||||
plt.xlabel('y', loc='right')
|
||||
plt.ylabel('x', loc='top')
|
||||
|
||||
# 显示网格线
|
||||
plt.grid(color='black', linestyle='-', linewidth=0.5)
|
||||
|
||||
# 显示图像
|
||||
plt.show()
|
||||
#plt.pause(0.01)
|
||||
|
||||
|
||||
def discretize_map(scene, scale_ratio):
|
||||
X = int(950 / scale_ratio) # 采点数量
|
||||
Y = int(1850 / scale_ratio)
|
||||
map = np.zeros((X, Y))
|
||||
|
||||
for x in range(X):
|
||||
for y in range(Y):
|
||||
if not scene.reachable_check(x * scale_ratio - 350, y * scale_ratio - 400, Yaw=0):
|
||||
map[x, y] = 1
|
||||
print(x, y)
|
||||
|
||||
file_name = 'map_'+str(scale_ratio)+'.pkl'
|
||||
if not os.path.exists(file_name):
|
||||
open(file_name, 'w').close()
|
||||
with open(file_name, 'wb') as file:
|
||||
pickle.dump(map, file)
|
||||
print('保存成功')
|
||||
|
||||
|
||||
def expand_obstacles(scale_ratio, expand_range=1):
|
||||
'''
|
||||
障碍物边沿扩展
|
||||
TODO: 扩展后的地图不可用！！！
|
||||
'''
|
||||
file_name = 'map_'+str(scale_ratio)+'.pkl'
|
||||
dilated_file_name = 'map_'+str(scale_ratio)+'_e'+str(expand_range)+'.pkl'
|
||||
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
|
||||
|
||||
dilated_map = binary_dilation(map, iterations=expand_range)
|
||||
|
||||
if not os.path.exists(dilated_file_name):
|
||||
open(dilated_file_name, 'w').close()
|
||||
with open(dilated_file_name, 'wb') as file:
|
||||
pickle.dump(dilated_map, file)
|
||||
print('保存成功')
|
||||
|
||||
|
||||
def show_map(file_name):
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
|
||||
draw_grid_map(map)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# scene.init_world(scene_num=1, mapID=11)
|
||||
# scene = scene.Scene(sceneID=0)
|
||||
#
|
||||
# # 离散化地图
|
||||
# discretize_map(scene, scale_ratio=4)
|
||||
|
||||
# # 扩张构型空间
|
||||
# expand_obstacles(scale_ratio=3, expand_range=1)
|
||||
|
||||
# 展示离散化地图
|
||||
file_name = 'costMap_4.pkl'
|
||||
show_map(file_name)
|
||||
|
|
@ -5,8 +5,8 @@
|
|||
'''
|
||||
|
||||
import math
|
||||
import queue
|
||||
from functools import partial
|
||||
import os
|
||||
import pickle
|
||||
import numpy as np
|
||||
import heapq
|
||||
|
||||
|
|
@ -115,13 +115,12 @@ class PriorityQueue:
|
|||
|
||||
class DStarLite:
|
||||
def __init__(self,
|
||||
map: np.array([int, int]), # [X, Y]
|
||||
area_range, # [x_min, x_max, y_min, y_max] 实际坐标范围
|
||||
scale_ratio=5, # 地图缩放率
|
||||
dyna_obs_radius=30, # dyna_obs实际身位半径
|
||||
map: np.array([int, int]),
|
||||
area_range, # [x_min, x_max, y_min, y_max] 实际坐标范围
|
||||
scale_ratio=5, # 地图缩放率
|
||||
dyna_obs_radius=36, # dyna_obs实际身位半径
|
||||
):
|
||||
|
||||
# self.area_bounds = area
|
||||
self.map = map
|
||||
self.background = map.copy()
|
||||
self.X = map.shape[0]
|
||||
|
|
@ -145,9 +144,13 @@ class DStarLite:
|
|||
"obstacle": float('inf'),
|
||||
"dynamic obstacle": 100
|
||||
}
|
||||
self.cost_map = np.zeros_like(self.map)
|
||||
|
||||
file_name = 'costMap_'+str(self.scale_ratio)+'.pkl'
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
cost_map = pickle.load(file)
|
||||
self.cost_map = cost_map
|
||||
self.cost_background = self.cost_map.copy()
|
||||
self.compute_cost_map()
|
||||
|
||||
self.s_start = None # (int,int) 必须是元组(元组可以直接当作矩阵索引)
|
||||
self.s_goal = None # (int,int)
|
||||
|
|
@ -163,9 +166,11 @@ class DStarLite:
|
|||
# 设置map 和 cost_map
|
||||
# '''
|
||||
# self.map = map_
|
||||
# self.background = map_.copy()
|
||||
# self.X = map_.shape[0]
|
||||
# self.Y = map_.shape[1]
|
||||
# self.compute_cost_map()
|
||||
# self.cost_background = self.cost_map.copy()
|
||||
|
||||
def reset(self):
|
||||
'''
|
||||
|
|
@ -299,11 +304,6 @@ class DStarLite:
|
|||
self.compute_shortest_path()
|
||||
self.path = self.get_path()
|
||||
return self.path
|
||||
# TODO: 误差抖动使robot没有到达路径上的点，导致新起点的rhs=∞，可能导致get_path失败 ( 当前版本没有该问题 )
|
||||
# assert (self.rhs[self.s_start] != float('inf')), "There is no known path!"
|
||||
# # debug
|
||||
# if debug:
|
||||
# pass
|
||||
|
||||
def planning(self, s_start, s_goal, dyna_obs, debug=False):
|
||||
'''
|
||||
|
|
@ -311,7 +311,10 @@ class DStarLite:
|
|||
'''
|
||||
# 实际坐标 -> 地图坐标
|
||||
s_start = self.real2map(s_start)
|
||||
s_goal = self.real2map(s_goal)
|
||||
if self.s_goal is None:
|
||||
s_goal = self.real2map(s_goal)
|
||||
else:
|
||||
s_goal = self.s_goal
|
||||
dyna_obs = [self.real2map(obs, reachable_assurance=False) for obs in dyna_obs]
|
||||
|
||||
self._planning(s_start, s_goal, dyna_obs, debug)
|
||||
|
|
@ -336,13 +339,6 @@ class DStarLite:
|
|||
succ = [s_ for s_ in self.get_neighbors(cur) if s_ not in path] # 避免抖动 (不可走重复的点)
|
||||
cur = succ[np.argmin([self.c(cur, s_) + self.g[s_] for s_ in succ])]
|
||||
path.append(cur)
|
||||
# else:
|
||||
# for i in range(step_num):
|
||||
# if cur == self.s_goal:
|
||||
# break
|
||||
# succ = self.get_neighbors(cur)
|
||||
# cur = succ[np.argmin([self.c(cur, s_) + self.g[s_] for s_ in succ])]
|
||||
# path.append(cur)
|
||||
return path
|
||||
|
||||
def in_bounds_without_obstacle(self, pos):
|
||||
|
|
@ -357,8 +353,6 @@ class DStarLite:
|
|||
获取邻居节点, 地图范围内
|
||||
'''
|
||||
(x_, y_) = pos
|
||||
# results = [(x_+1,y_), (x_-1,y_), (x_, y_+1), (x_,y_-1)]
|
||||
# if mode == 8:
|
||||
neighbors = [(x_ + 1, y_), (x_ - 1, y_), (x_, y_ + 1), (x_, y_ - 1), (x_ + 1, y_ + 1), (x_ - 1, y_ + 1),
|
||||
(x_ + 1, y_ - 1), (x_ - 1, y_ - 1)]
|
||||
neighbors = filter(self.in_bounds_without_obstacle, neighbors) # 确保位置在地图范围内 且 不是静态障碍物
|
||||
|
|
@ -366,17 +360,26 @@ class DStarLite:
|
|||
|
||||
def compute_cost_map(self):
|
||||
# 计算当前地图的cost_map
|
||||
self.cost_map = np.zeros_like(self.map)
|
||||
for idx, obj in self.idx_to_object.items():
|
||||
self.cost_map[self.map == idx] = self.object_to_cost[obj]
|
||||
|
||||
# # TODO
|
||||
# for x in range(self.X):
|
||||
# for y in range(self.Y):
|
||||
# if self.cost_map[x, y] > 0:
|
||||
# neighbors = self.get_neighbors((x, y))
|
||||
# for (x_, y_) in neighbors:
|
||||
# self.cost_map[x_, y_] = max(self.cost_map[x_, y_], self.cost_map[x, y] - 10)
|
||||
|
||||
# 扩张静态障碍物影响范围
|
||||
obs_pos = np.where(self.map == self.object_to_idx['obstacle']) # 静态障碍物位置列表
|
||||
for (x, y) in zip(obs_pos[0], obs_pos[1]):
|
||||
start_x, end_x = max(x - 1, 0), min(x + 1, self.X - 1)
|
||||
start_y, end_y = max(y - 1, 0), min(y + 1, self.Y - 1)
|
||||
for cost in range(9, 0, -3):
|
||||
for x_ in range(start_x, end_x + 1):
|
||||
self.cost_map[x_, start_y] = max(self.cost_map[x_, start_y], cost)
|
||||
for y_ in range(start_y + 1, end_y + 1):
|
||||
self.cost_map[end_x, y_] = max(self.cost_map[end_x, y_], cost)
|
||||
for x_ in range(end_x - 1, start_x - 1, -1):
|
||||
self.cost_map[x_, end_y] = max(self.cost_map[x_, end_y], cost)
|
||||
for y_ in range(end_y - 1, start_y, -1):
|
||||
self.cost_map[start_x, y_] = max(self.cost_map[start_x, y_], cost)
|
||||
start_x, end_x = max(start_x - 1, 0), min(end_x + 1, self.X - 1)
|
||||
start_y, end_y = max(start_y - 1, 0), min(end_y + 1, self.Y - 1)
|
||||
|
||||
self.cost_background = self.cost_map.copy()
|
||||
|
||||
|
|
@ -388,8 +391,8 @@ class DStarLite:
|
|||
return:
|
||||
update_obj: 改变的位置列表 [(x, y, obj_idx, obj_idx_old), ...]
|
||||
'''
|
||||
# dyna_obs没有变化 (集合set可以忽略元素在列表中的位置)
|
||||
if set(dyna_obs) == set(self.dyna_obs_list):
|
||||
# dyna_obs没有变化 (集合set可以忽略元素在列表中的位置) 且 robot未在dyna_obs占用位置中
|
||||
if set(dyna_obs) == set(self.dyna_obs_list) and self.s_start not in self.dyna_obs_occupy:
|
||||
return []
|
||||
|
||||
# 当前dyna_obs占用位置列表
|
||||
|
|
@ -397,24 +400,10 @@ class DStarLite:
|
|||
for pos in dyna_obs:
|
||||
dyna_obs_occupy.extend(self.get_occupy_pos(pos))
|
||||
dyna_obs_occupy = [pos for i, pos in enumerate(dyna_obs_occupy) if pos not in dyna_obs_occupy[:i]] # 去除重复位置
|
||||
# 转变为free 和 转变为obs的位置列表
|
||||
# 转变为free 和 转变为dyna_obs的位置列表
|
||||
changed_free = [pos for pos in self.dyna_obs_occupy if pos not in dyna_obs_occupy]
|
||||
changed_obs = [pos for pos in dyna_obs_occupy if pos not in self.dyna_obs_occupy]
|
||||
|
||||
# # 新旧dyna_obs占用位置列表
|
||||
# old_obs_occupy = []
|
||||
# new_obs_occupy = []
|
||||
# for pos in self.dyna_obs_list:
|
||||
# old_obs_occupy.extend(self.get_occupy_pos(pos))
|
||||
# for pos in dyna_obs:
|
||||
# new_obs_occupy.extend(self.get_occupy_pos(pos))
|
||||
# old_obs_occupy = [pos for i, pos in enumerate(old_obs_occupy) if pos not in old_obs_occupy[:i]] # 去除重复位置
|
||||
# new_obs_occupy = [pos for i, pos in enumerate(new_obs_occupy) if pos not in new_obs_occupy[:i]] # 去除重复位置
|
||||
#
|
||||
# # 转变为free 和 转变为obs的位置列表
|
||||
# changed_free = [pos for pos in old_obs_occupy if pos not in new_obs_occupy]
|
||||
# changed_obs = [pos for pos in new_obs_occupy if pos not in old_obs_occupy]
|
||||
|
||||
# 更新地图，计算changed_pos
|
||||
changed_pos = []
|
||||
for (x, y) in changed_free:
|
||||
|
|
@ -430,21 +419,15 @@ class DStarLite:
|
|||
|
||||
return changed_pos
|
||||
|
||||
|
||||
|
||||
def get_occupy_pos(self, obs_pos):
|
||||
'''
|
||||
根据dyna_obs中心位置，计算其占用的所有网格位置
|
||||
'''
|
||||
(x, y) = obs_pos
|
||||
occupy_radius = min(self.dyna_obs_radius, int(euclidean_distance(obs_pos, self.s_start) - 1)) # 避免robot被dyna_obs的占用区域包裹住
|
||||
# for i in range(x - self.dyna_obs_radius, x + self.dyna_obs_radius + 1): # 方形区域
|
||||
# for j in range(y - self.dyna_obs_radius, y + self.dyna_obs_radius + 1):
|
||||
# occupy_pos.append((i, j))
|
||||
occupy_pos = [(i, j) for i in range(x - occupy_radius, x + occupy_radius + 1) # 圆形区域
|
||||
for j in range(y - occupy_radius, y + occupy_radius + 1)
|
||||
if euclidean_distance((i, j), obs_pos) < occupy_radius]
|
||||
|
||||
occupy_pos = filter(self.in_bounds_without_obstacle, occupy_pos) # 确保位置在地图范围内 且 不是静态障碍物
|
||||
return list(occupy_pos)
|
||||
|
||||
|
|
@ -497,21 +480,40 @@ class DStarLite:
|
|||
'''
|
||||
x = round((pos[0] - self.x_min) / self.scale_ratio)
|
||||
y = round((pos[1] - self.y_min) / self.scale_ratio)
|
||||
# 需要确保点可达
|
||||
if reachable_assurance and self.idx_to_object[self.map[x, y]] != 'free':
|
||||
print('1')
|
||||
x_ = math.floor((pos[0] - self.x_min) / self.scale_ratio)
|
||||
y_ = math.floor((pos[1] - self.y_min) / self.scale_ratio)
|
||||
candidates = [(x_, y_), (x_ + 1, y_), (x_, y_ + 1), (x_ + 1, y_ + 1)]
|
||||
for (x, y) in candidates:
|
||||
print(self.idx_to_object[self.map[x, y]])
|
||||
if self.idx_to_object[self.map[x, y]] == 'free':
|
||||
print((x,y))
|
||||
return tuple((x, y))
|
||||
raise Exception('error')
|
||||
# 确保点不在静态障碍物上，否则就不断向外圈扩展直到找到非静态障碍物位置
|
||||
if reachable_assurance:
|
||||
return self.validate_pos((x, y))
|
||||
else:
|
||||
return tuple((x, y))
|
||||
|
||||
def validate_pos(self, pos):
|
||||
'''
|
||||
对于不合法的pos，找到周围距离最近的合法坐标
|
||||
'''
|
||||
(x, y) = pos
|
||||
x = max(0, min(x, self.X - 1))
|
||||
y = max(0, min(y, self.Y - 1))
|
||||
if self.idx_to_object[self.map[x, y]] == 'obstacle':
|
||||
start_x, end_x = max(x - 1, 0), min(x + 1, self.X - 1)
|
||||
start_y, end_y = max(y - 1, 0), min(y + 1, self.Y - 1)
|
||||
while True:
|
||||
for x_ in range(start_x, end_x + 1):
|
||||
if self.idx_to_object[self.map[x_, start_y]] != 'obstacle':
|
||||
return tuple((x_, start_y))
|
||||
for y_ in range(start_y + 1, end_y + 1):
|
||||
if self.idx_to_object[self.map[end_x, y_]] != 'obstacle':
|
||||
return tuple((end_x, y_))
|
||||
for x_ in range(end_x - 1, start_x - 1, -1):
|
||||
if self.idx_to_object[self.map[x_, end_y]] != 'obstacle':
|
||||
return tuple((x_, end_y))
|
||||
for y_ in range(end_y - 1, start_y, -1):
|
||||
if self.idx_to_object[self.map[start_x, y_]] != 'obstacle':
|
||||
return tuple((start_x, y_))
|
||||
start_x, end_x = max(start_x - 1, 0), min(end_x + 1, self.X - 1)
|
||||
start_y, end_y = max(start_y - 1, 0), min(end_y + 1, self.Y - 1)
|
||||
# raise Exception('invalid pos!')
|
||||
return tuple((x, y))
|
||||
|
||||
def draw_graph(self, step_num):
|
||||
# 清空当前figure内容，保留figure对象
|
||||
plt.clf()
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 25 KiB |
Binary file not shown.
Binary file not shown.
|
|
@ -0,0 +1,115 @@
|
|||
#!/usr/bin/env python3
|
||||
# -*- encoding: utf-8 -*-
|
||||
import math
|
||||
import os
|
||||
import pickle
|
||||
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
from robowaiter.scene import scene
|
||||
|
||||
from robowaiter.algos.navigator.dstar_lite import DStarLite, euclidean_distance
|
||||
|
||||
|
||||
|
||||
class Navigator:
|
||||
'''
|
||||
导航类
|
||||
'''
|
||||
|
||||
def __init__(self, scene, area_range, map, scale_ratio=5, step_length=150, velocity=150, react_radius=300):
|
||||
self.scene = scene
|
||||
self.area_range = area_range # 地图实际坐标范围 xmin, xmax, ymin, ymax
|
||||
self.map = map # 缩放并离散化的地图 array(X,Y)
|
||||
self.scale_ratio = scale_ratio # 地图缩放率
|
||||
self.step_length = step_length # 步长(单次移动)
|
||||
self.step_num = self.step_length // self.scale_ratio # 单次移动地图格数
|
||||
self.v = velocity # 速度
|
||||
self.react_radius = react_radius # robot反应半径
|
||||
|
||||
self.planner = DStarLite(area_range=area_range, map=map, scale_ratio=scale_ratio)
|
||||
|
||||
def validate_goal(self, goal):
|
||||
'''
|
||||
目标合法化
|
||||
'''
|
||||
return self.planner.map2real(self.planner.real2map(goal))
|
||||
|
||||
@staticmethod
|
||||
def is_reached(pos: (float, float), goal: (float, float), dis_limit=50):
|
||||
'''
|
||||
判断是否到达目标
|
||||
'''
|
||||
dis = math.hypot(pos[0]-goal[0], pos[1]-goal[1])
|
||||
# dis = np.linalg.norm(pos - goal)
|
||||
return dis < dis_limit
|
||||
|
||||
@staticmethod
|
||||
def get_yaw(pos: (float, float), goal: (float, float)):
|
||||
'''
|
||||
得到移动方向
|
||||
'''
|
||||
# return math.degrees(math.atan2(goal[0] - pos[0], -(goal[1] - pos[1])))
|
||||
return math.degrees(math.atan2((goal[1] - pos[1]), (goal[0] - pos[0])))
|
||||
|
||||
def navigate(self, goal: (float, float), animation=True):
|
||||
'''
|
||||
单次导航，直到到达目标
|
||||
'''
|
||||
goal = self.validate_goal(goal) # 目标合法化
|
||||
pos = (self.scene.status.location.X, self.scene.status.location.Y) # 机器人当前: 位置 和 朝向
|
||||
print('------------------navigation_start----------------------')
|
||||
while not self.is_reached(pos, goal):
|
||||
dyna_obs = [(walker.pose.X, walker.pose.Y) for walker in self.scene.status.walkers] # 动态障碍物(顾客)位置列表
|
||||
dyna_obs = [obs for obs in dyna_obs if euclidean_distance(obs, pos) < self.react_radius] # 过滤观测范围外的dyna_obs
|
||||
# 周围有dyna_obs则步长减半
|
||||
if dyna_obs:
|
||||
step_num = self.step_num // 2
|
||||
else:
|
||||
step_num = self.step_num
|
||||
path = self.planner.planning(pos, goal, dyna_obs)
|
||||
if path:
|
||||
if animation:
|
||||
self.planner.draw_graph(step_num) # 画出搜索路径
|
||||
next_step = min(step_num, len(path))
|
||||
next_pos = path[next_step - 1]
|
||||
print('plan pos:', next_pos, end=' ')
|
||||
yaw = self.get_yaw(pos, next_pos)
|
||||
self.scene.walk_to(next_pos[0], next_pos[1], yaw, velocity=self.v, dis_limit=10)
|
||||
self.planner.path = self.planner.path[next_step - 1:] # 去除已走过的路径
|
||||
pos = (self.scene.status.location.X, self.scene.status.location.Y)
|
||||
print('reach pos:', pos)
|
||||
|
||||
self.planner.reset() # 完成一轮导航，重置变量
|
||||
|
||||
if self.is_reached(pos, goal):
|
||||
print('The robot has achieved goal !!')
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
||||
# 根据map计算并保存cost_map
|
||||
|
||||
file_name = 'map_4.pkl'
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
|
||||
|
||||
scene.init_world(1, 11)
|
||||
scene = scene.Scene(sceneID=0)
|
||||
|
||||
navigator = Navigator(scene=scene, area_range=[-350, 600, -400, 1450], map=map, scale_ratio=4)
|
||||
|
||||
navigator.planner.compute_cost_map()
|
||||
|
||||
file_name = 'costMap_4.pkl'
|
||||
if not os.path.exists(file_name):
|
||||
open(file_name, 'w').close()
|
||||
with open(file_name, 'wb') as file:
|
||||
pickle.dump(navigator.planner.cost_map, file)
|
||||
print('保存成功')
|
||||
|
|
@ -0,0 +1,128 @@
|
|||
# D_star Lite 机器人任务规划
|
||||
## 目录结构
|
||||
### 坐标离散化
|
||||
`discretize_map.py`
|
||||
|
||||
### 地图文件(选择缩放倍率)
|
||||
`map_3.pkl`
|
||||
`map_4.pkl`
|
||||
`map_5.pkl`
|
||||
|
||||
### 导航类
|
||||
`navigate.py`
|
||||
|
||||
### D_star Lite 算法实现
|
||||
`dstar_lite.py`
|
||||
|
||||
### 测试文件
|
||||
`test.py`
|
||||
|
||||
---
|
||||
|
||||
## 世界地图
|
||||
|
||||
### 实际坐标范围
|
||||
|
||||
`X: -350 ~ 600`
|
||||
|
||||
`Y: -400 ~ 1450`
|
||||
|
||||
### 5倍缩放后坐标范围
|
||||
|
||||
`X: -70 ~ 120`
|
||||
|
||||
`Y: -80 ~ 290`
|
||||
|
||||
### 网格地图
|
||||
|
||||
| Idx | Obj |
|
||||
|-----|------------------|
|
||||
| 0 | free |
|
||||
| 1 | obstacle |
|
||||
| 2 | dynamic obstacle |
|
||||
|
||||
### 代价地图
|
||||
| Cost | Obj |
|
||||
|---------|-----------------|
|
||||
| 0 | free |
|
||||
| 15-10-5 | obs周围3格 |
|
||||
| inf | obstacle |
|
||||
| 100 | dynamic obstacle |
|
||||
|
||||
|
||||
---
|
||||
|
||||
|
||||
## 参数
|
||||
`机器人步长`： 150
|
||||
|
||||
`机器人速度`： 150
|
||||
|
||||
`机器人观测范围`： 300
|
||||
|
||||
`行人半径`： 36
|
||||
|
||||
`目标判达距离`： 50
|
||||
|
||||
`机器人移动dis_limit`： 10
|
||||
|
||||
---
|
||||
|
||||
## 使用方法
|
||||
```python
|
||||
# 选择缩放合适的地图：3、4、5
|
||||
file_name = 'map_4.pkl'
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
|
||||
|
||||
# 初始化场景
|
||||
scene.init_world(1, 11)
|
||||
scene = scene.Scene(sceneID=0)
|
||||
|
||||
# 舒适化导航类
|
||||
# (需要传入：场景、实际地图范围、离散化地图、缩放比例)
|
||||
navigator = Navigator(scene=scene, area_range=[-350, 600, -400, 1450], map=map, scale_ratio=4)
|
||||
|
||||
# 设置目标
|
||||
goal = (0, 0)
|
||||
|
||||
# 导航
|
||||
# (animation: 选择是否画出导航过程)
|
||||
navigator.navigate(goal, animation=False)
|
||||
|
||||
```
|
||||
|
||||
|
||||
---
|
||||
|
||||
## 可靠性保证
|
||||
|
||||
`目标合法性保证`：
|
||||
|
||||
- 目标在地图外：重置目标为最近的地图内位置
|
||||
- 目标在静态障碍物：从当前位置不断向外圈扩展直到找到合法位置，重置目标为该位置
|
||||
|
||||
`规划sbgoal合法性保证`：
|
||||
|
||||
- 规划subgoal被动态障碍物占据：重新规划路径
|
||||
|
||||
|
||||
`起点合法性保证`：
|
||||
|
||||
- 起点在静态障碍物：从当前位置不断向外圈扩展直到找到合法位置，重置起点为该位置
|
||||
- 起点在动态障碍物范围内：缩小动态障碍物半径，保证起点位置为空闲
|
||||
|
||||
|
||||
`机器人朝向保证`：
|
||||
|
||||
- 机器人始终朝向每一步的移动方向
|
||||
|
||||
|
||||
`规划抖动解决`：
|
||||
|
||||
- 规划路径不允许有重复点
|
||||
|
||||
`避免机器人沿障碍物行走`：
|
||||
|
||||
- 障碍物扩张：在代价地图`cost_map`中，静态障碍物周围的空位也会受到影响，并产生cost
|
||||
|
|
@ -1,22 +1,19 @@
|
|||
import os
|
||||
import pickle
|
||||
import time
|
||||
import random
|
||||
import math
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
|
||||
from robowaiter.scene import scene
|
||||
# from navigate import Navigator
|
||||
from robowaiter.algos.navigate.navigate import Navigator
|
||||
from robowaiter.algos.navigator.navigate import Navigator
|
||||
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# def navigate_test(scene):
|
||||
|
||||
file_name = 'map_5.pkl'
|
||||
# 选择缩放合适的地图：3、4、5
|
||||
file_name = 'map_4.pkl'
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
|
||||
|
|
@ -24,21 +21,25 @@ if __name__ == '__main__':
|
|||
scene.init_world(1, 11)
|
||||
scene = scene.Scene(sceneID=0)
|
||||
|
||||
navigator = Navigator(scene=scene, area_range=[-350, 600, -400, 1450], map=map)
|
||||
navigator = Navigator(scene=scene, area_range=[-350, 600, -400, 1450], map=map, scale_ratio=4)
|
||||
|
||||
'''场景1: 无行人环境 robot到达指定目标'''
|
||||
# goal = np.array((-100, 700))
|
||||
# goal = (-100, 700)
|
||||
# goal = (590, 1370)
|
||||
# goal = (290, -240)
|
||||
# goal = (-200, -200)
|
||||
# goal = (-200, -50)
|
||||
|
||||
'''场景2: 静止行人环境 robot到达指定目标'''
|
||||
# scene.clean_walker()
|
||||
# scene.add_walker(50, 300, 0)
|
||||
# scene.add_walker(-50, 500, 0)
|
||||
# goal = np.array((-100, 700))
|
||||
# goal = (-100, 700)
|
||||
|
||||
'''场景3: 移动行人环境 robot到达指定目标'''
|
||||
scene.walk_to(100, 0, -90, dis_limit=10)
|
||||
scene.walk_to(100, 0, -90, dis_limit=5)
|
||||
scene.clean_walker()
|
||||
scene.add_walkers([[50, 300],[-50, 500],[0, 700]])
|
||||
scene.add_walkers([[50, 300], [-50, 500], [0, 700]])
|
||||
# scene.add_walker(50, 300, 0)
|
||||
# scene.add_walker(-50, 500, 0)
|
||||
# scene.add_walker(0, 700, 0)
|
||||
|
|
@ -47,12 +48,13 @@ if __name__ == '__main__':
|
|||
scene.control_walker([scene.walker_control_generator(walkerID=2, autowalk=False, speed=50, X=0, Y=0, Yaw=0)])
|
||||
|
||||
# goal = (-100, 700)
|
||||
# goal = (-300)
|
||||
# goal = (340.0, 900.0)
|
||||
# goal = (-200, 700) # 目标在障碍物测试
|
||||
# goal = (-400, 700) # 目标在地图外测试
|
||||
goal = (10000, 10000) # 目标在地图外测试
|
||||
# goal = (-220, 300)
|
||||
# goal = (-280, 400)
|
||||
# goal = (-230, 600)
|
||||
|
||||
# goal = (240.0, 1000.0)
|
||||
# goal = (340.0, 900.0)
|
||||
goal = (240.0, 1160.0)
|
||||
|
||||
'''场景4: 行人自由移动 robot到达指定目标'''
|
||||
# # TODO: autowalk=True仿真器会闪退 ???
|
||||
|
|
@ -62,7 +64,7 @@ if __name__ == '__main__':
|
|||
# scene.control_walker([scene.walker_control_generator(walkerID=0, autowalk=True, speed=20, X=0, Y=0, Yaw=0)])
|
||||
# scene.control_walker([scene.walker_control_generator(walkerID=1, autowalk=True, speed=20, X=0, Y=0, Yaw=0)])
|
||||
# time.sleep(5)
|
||||
# goal = np.array((-100, 700))
|
||||
# goal = (-100, 700)
|
||||
|
||||
navigator.navigate(goal, animation=True)
|
||||
|
||||
|
|
@ -13,12 +13,12 @@ class Bahavior(ptree.behaviour.Behaviour):
|
|||
'''
|
||||
scene = None
|
||||
print_name_prefix = ""
|
||||
all_place = {'Bar', 'Bar2', 'WaterTable', 'CoffeeTable', 'Table1', 'Table2', 'Table3'}
|
||||
# all_place = {'Bar', 'Bar2', 'WaterTable', 'CoffeeTable', 'Table1', 'Table2', 'Table3'}
|
||||
# all_object = {'Coffee', 'Water', 'Dessert', 'Softdrink', 'BottledDrink', 'Yogurt', 'ADMilk', 'MilkDrink', 'Milk',
|
||||
# 'VacuumCup'}
|
||||
# all_place = {'Bar', 'WaterTable', 'CoffeeTable'}
|
||||
all_place = {'Bar', 'WaterTable', 'CoffeeTable'}
|
||||
# all_object = {'Coffee', 'Water', 'Dessert', 'Softdrink', 'Yogurt'}
|
||||
all_object = {'Coffee'}
|
||||
all_object = {'Coffee', 'Water'}
|
||||
place_xyz_dic={
|
||||
'Bar': (247.0, 520.0, 100.0),
|
||||
'Bar2': (240.0, 40.0, 70.0),
|
||||
|
|
@ -28,6 +28,13 @@ class Bahavior(ptree.behaviour.Behaviour):
|
|||
'Table2': (-55.0, 0.0, 107),
|
||||
'Table3':(-55.0, 150.0, 107)
|
||||
}
|
||||
container_dic={
|
||||
'Coffee':'CoffeeCup',
|
||||
'Water': 'Glass',
|
||||
'Dessert':'Plate'
|
||||
}
|
||||
|
||||
|
||||
|
||||
@classmethod
|
||||
def get_ins_name(cls,*args):
|
||||
|
|
|
|||
|
|
@ -14,11 +14,11 @@ class Make(Act):
|
|||
super().__init__(*args)
|
||||
self.target_obj = self.args[0]
|
||||
self.op_type = 1
|
||||
if self.target_obj=="Coffee":
|
||||
if self.target_obj==self.valid_args[0]:
|
||||
self.op_type = 1
|
||||
elif self.target_obj=="Water":
|
||||
elif self.target_obj==self.valid_args[1]:
|
||||
self.op_type = 2
|
||||
elif self.target_obj=="Dessert":
|
||||
elif self.target_obj==self.valid_args[2]:
|
||||
self.op_type = 3
|
||||
|
||||
|
||||
|
|
@ -28,12 +28,12 @@ class Make(Act):
|
|||
info["pre"]= {f'Holding(Nothing)'}
|
||||
info['del_set'] = set()
|
||||
info['add'] = {f'Exist({arg})'}
|
||||
if arg == "Coffee":
|
||||
info["add"] |= {f'On(Coffee,CoffeeTable)'}
|
||||
elif arg == "Water":
|
||||
info["add"] |= {f'On(Water,WaterTable)'}
|
||||
elif arg == "Dessert":
|
||||
info["add"] |= {f'On(Dessert,Bar)'}
|
||||
if arg == cls.valid_args[0]:
|
||||
info["add"] |= {f'On({arg},CoffeeTable)'}
|
||||
elif arg == cls.valid_args[1]:
|
||||
info["add"] |= {f'On({arg},WaterTable)'}
|
||||
elif arg == cls.valid_args[2]:
|
||||
info["add"] |= {f'On({arg},Bar)'}
|
||||
return info
|
||||
|
||||
def _update(self) -> ptree.common.Status:
|
||||
|
|
@ -43,16 +43,20 @@ class Make(Act):
|
|||
|
||||
# self.scene.gen_obj(type=40)
|
||||
|
||||
obj_dict = self.scene.status.objects
|
||||
if len(obj_dict) != 0:
|
||||
# 获取obj_id
|
||||
for id, obj in enumerate(obj_dict):
|
||||
if obj.name == "Coffee":
|
||||
obj_info = obj_dict[id]
|
||||
obj_x, obj_y, obj_z = obj_info.location.X, obj_info.location.Y, obj_info.location.Z
|
||||
print(id,obj.name,obj_x,obj_y,obj_z)
|
||||
# obj_dict = self.scene.status.objects
|
||||
# if len(obj_dict) != 0:
|
||||
# # 获取obj_id
|
||||
# for id, obj in enumerate(obj_dict):
|
||||
# print("id:",id,"obj",obj.name)
|
||||
|
||||
# if obj.name == "Coffee":
|
||||
# obj_info = obj_dict[id]
|
||||
# obj_x, obj_y, obj_z = obj_info.location.X, obj_info.location.Y, obj_info.location.Z
|
||||
# print(id,obj.name,obj_x,obj_y,obj_z)
|
||||
|
||||
self.scene.state["condition_set"] |= (self.info["add"])
|
||||
self.scene.state["condition_set"] -= self.info["del_set"]
|
||||
|
||||
# print("condition_set:",self.scene.state["condition_set"])
|
||||
|
||||
return Status.RUNNING
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
import py_trees as ptree
|
||||
from robowaiter.behavior_lib._base.Act import Act
|
||||
from robowaiter.algos.navigate.navigate import Navigator
|
||||
from robowaiter.algos.navigator.navigate import Navigator
|
||||
|
||||
class MoveTo(Act):
|
||||
can_be_expanded = True
|
||||
|
|
@ -21,6 +21,7 @@ class MoveTo(Act):
|
|||
info['pre'] |= {f'Exist({arg})'}
|
||||
info["add"] = {f'At(Robot,{arg})'}
|
||||
info["del_set"] = {f'At(Robot,{place})' for place in cls.valid_args if place != arg}
|
||||
info['cost']=10
|
||||
return info
|
||||
|
||||
|
||||
|
|
@ -29,30 +30,39 @@ class MoveTo(Act):
|
|||
|
||||
# navigator = Navigator(scene=self.scene, area_range=[-350, 600, -400, 1450], map=self.scene.state["map"]["2d"])
|
||||
# goal = self.scene.state['map']['obj_pos'][self.args[0]]
|
||||
# navigator.navigate(goal, animation=False)
|
||||
# navigator.navigate_old(goal, animation=False)
|
||||
|
||||
# 走到固定的地点
|
||||
if self.target_place in Act.place_xyz_dic:
|
||||
goal = Act.place_xyz_dic[self.target_place]
|
||||
self.scene.walk_to(goal[0],goal[1])
|
||||
else: # 走到物品边上
|
||||
self.scene.walk_to(goal[0]+1,goal[1])
|
||||
# 走到物品边上
|
||||
else:
|
||||
# 是否用容器装好
|
||||
if self.target_place in Act.container_dic:
|
||||
target_name = Act.container_dic[self.target_place]
|
||||
else:
|
||||
target_name = self.target_place
|
||||
# 根据物体名字找到最近的这类物体对应的位置
|
||||
obj_id = -1
|
||||
min_dis = float('inf')
|
||||
obj_dict = self.scene.status.objects
|
||||
if len(obj_dict)!=0:
|
||||
# 获取obj_id
|
||||
for id,obj in enumerate(obj_dict):
|
||||
if obj.name == self.target_place:
|
||||
obj_id = id
|
||||
# obj_info = obj_dict[id]
|
||||
# obj_x, obj_y, obj_z = obj_info.location.X, obj_info.location.Y, obj_info.location.Z
|
||||
# ginger_x,ginger_y,ginger_z = [int(self.scene.location.X), int(self.scene.location.Y), int(self.scene.rotation.Yaw)]
|
||||
break
|
||||
if self.target_place == "CoffeeCup":
|
||||
obj_id = 273
|
||||
if obj.name == target_name:
|
||||
obj_info = obj_dict[id]
|
||||
dis = self.scene.cal_distance_to_robot(obj_info.location.X, obj_info.location.Y, obj_info.location.Z)
|
||||
if dis<min_dis:
|
||||
min_dis = dis
|
||||
obj_id = id
|
||||
# if self.target_place == "CoffeeCup":
|
||||
# # obj_id = 273
|
||||
# obj_id = 275
|
||||
if obj_id == -1:
|
||||
return ptree.common.Status.FAILURE
|
||||
|
||||
# print("self.target_place:",self.target_place,"id:",obj_id,"dis:",min_dis)
|
||||
self.scene.move_to_obj(obj_id=obj_id)
|
||||
|
||||
# 为了演示，写死咖啡位置
|
||||
|
|
|
|||
|
|
@ -25,14 +25,36 @@ class PickUp(Act):
|
|||
|
||||
def _update(self) -> ptree.common.Status:
|
||||
# self.scene.test_move()
|
||||
op_type=16
|
||||
obj_id = 0
|
||||
# op_type=16
|
||||
|
||||
# 遍历场景里的所有物品，根据名字匹配位置最近的 obj-id
|
||||
# 是否用容器装好
|
||||
if self.target_obj in Act.container_dic:
|
||||
target_name = Act.container_dic[self.target_obj]
|
||||
else:
|
||||
target_name = self.target_obj
|
||||
# 根据物体名字找到最近的这类物体对应的位置
|
||||
obj_id = -1
|
||||
min_dis = float('inf')
|
||||
obj_dict = self.scene.status.objects
|
||||
if len(obj_dict) != 0:
|
||||
# 获取obj_id
|
||||
for id, obj in enumerate(obj_dict):
|
||||
if obj.name == target_name:
|
||||
obj_info = obj_dict[id]
|
||||
dis = self.scene.cal_distance_to_robot(obj_info.location.X, obj_info.location.Y,
|
||||
obj_info.location.Z)
|
||||
if dis < min_dis:
|
||||
min_dis = dis
|
||||
obj_id = id
|
||||
# if self.target_place == "CoffeeCup":
|
||||
# # obj_id = 273
|
||||
# obj_id = 275
|
||||
if obj_id == -1:
|
||||
return ptree.common.Status.FAILURE
|
||||
|
||||
if self.args=="Coffee":
|
||||
obj_id = 273
|
||||
|
||||
self.scene.op_task_execute(op_type, obj_id=obj_id)
|
||||
self.scene.move_task_area(op_type=16, obj_id=obj_id)
|
||||
self.scene.op_task_execute(op_type=16, obj_id=obj_id)
|
||||
|
||||
self.scene.state["condition_set"] |= (self.info["add"])
|
||||
self.scene.state["condition_set"] -= self.info["del_set"]
|
||||
|
|
|
|||
|
|
@ -22,6 +22,8 @@ class PutDown(Act):
|
|||
info["pre"] = {f'Holding({arg[0]})',f'At(Robot,{arg[1]})'}
|
||||
info["add"] = {f'Holding(Nothing)',f'On({arg[0]},{arg[1]})'}
|
||||
info["del_set"] = {f'Holding({arg[0]})'}
|
||||
|
||||
info['cost'] = 100
|
||||
return info
|
||||
|
||||
|
||||
|
|
@ -31,8 +33,11 @@ class PutDown(Act):
|
|||
release_pos = list(Act.place_xyz_dic[self.target_place])
|
||||
# # 原始吧台处:[247.0, 520.0, 100.0], 空调开关旁吧台:[240.0, 40.0, 70.0], 水杯桌:[-70.0, 500.0, 107]
|
||||
# # 桌子2:[-55.0, 0.0, 107],桌子3:[-55.0, 150.0, 107]
|
||||
self.scene.move_task_area(op_type, release_pos=release_pos)
|
||||
self.scene.op_task_execute(op_type, release_pos=release_pos)
|
||||
|
||||
self.scene.state["condition_set"] |= (self.info["add"])
|
||||
self.scene.state["condition_set"] -= self.info["del_set"]
|
||||
|
||||
print("After PutDown condition_set:",self.scene.state["condition_set"])
|
||||
return Status.RUNNING
|
||||
|
|
|
|||
|
|
@ -16,6 +16,9 @@ class On(Cond):
|
|||
def _update(self) -> ptree.common.Status:
|
||||
# if self.scene.status?
|
||||
|
||||
# print("self.name:",self.name)
|
||||
# print("On: condition_set:",self.scene.state["condition_set"])
|
||||
|
||||
if self.name in self.scene.state["condition_set"]:
|
||||
return ptree.common.Status.SUCCESS
|
||||
else:
|
||||
|
|
|
|||
|
|
@ -2,6 +2,8 @@ import copy
|
|||
import random
|
||||
from robowaiter.behavior_tree.obtea.BehaviorTree import Leaf,ControlBT
|
||||
|
||||
|
||||
|
||||
class CondActPair:
|
||||
def __init__(self, cond_leaf,act_leaf):
|
||||
self.cond_leaf = cond_leaf
|
||||
|
|
@ -54,7 +56,10 @@ class OptBTExpAlgorithm:
|
|||
self.conditions_index = []
|
||||
|
||||
#运行规划算法，从初始状态、目标状态和可用行动，计算行为树self.bt
|
||||
def run_algorithm(self,goal,actions):
|
||||
def run_algorithm(self,goal,actions,scene):
|
||||
|
||||
self.scene = scene
|
||||
|
||||
if self.verbose:
|
||||
print("\n算法开始！")
|
||||
|
||||
|
|
@ -99,8 +104,13 @@ class OptBTExpAlgorithm:
|
|||
sequence_structure.add_child(
|
||||
[copy.deepcopy(pair_node.cond_leaf), copy.deepcopy(pair_node.act_leaf)])
|
||||
subtree.add_child([copy.deepcopy(sequence_structure)]) # subtree 是回不断变化的，它的父亲是self.bt
|
||||
# 增加实时条件判断，满足条件就不再扩展
|
||||
# if c <= self.scene.state["condition_set"]:
|
||||
# return True
|
||||
else:
|
||||
subtree.add_child([copy.deepcopy(pair_node.act_leaf)])
|
||||
|
||||
|
||||
if self.verbose:
|
||||
print("完成扩展 a_node= %s,对应的新条件 c_attr= %s,mincost=%d" \
|
||||
% (cond_anc_pair.act_leaf.content.name, cond_anc_pair.cond_leaf.content,
|
||||
|
|
@ -128,14 +138,14 @@ class OptBTExpAlgorithm:
|
|||
break
|
||||
|
||||
if valid:
|
||||
# 把符合条件的动作节点都放到列表里
|
||||
if self.verbose:
|
||||
print("———— -- %s 符合条件放入列表" % actions[i].name)
|
||||
c_attr_node = Leaf(type='cond', content=c_attr, mincost=current_mincost + actions[i].cost)
|
||||
a_attr_node = Leaf(type='act', content=actions[i], mincost=current_mincost + actions[i].cost)
|
||||
cond_anc_pair = CondActPair(cond_leaf=c_attr_node, act_leaf=a_attr_node)
|
||||
self.nodes.append(copy.deepcopy(cond_anc_pair)) # condition node list
|
||||
self.traversed.append(c_attr) # 重点 the set of expanded conditions
|
||||
# 把符合条件的动作节点都放到列表里
|
||||
if self.verbose:
|
||||
print("———— -- %s 符合条件放入列表,对应的c为 %s" % (actions[i].name,c_attr))
|
||||
|
||||
if self.verbose:
|
||||
print("算法结束！\n")
|
||||
|
|
@ -178,13 +188,23 @@ class OptBTExpAlgorithm:
|
|||
|
||||
|
||||
# 树的dfs
|
||||
def dfs_ptml(self,parnode):
|
||||
def dfs_ptml(self,parnode,is_root=False):
|
||||
for child in parnode.children:
|
||||
if isinstance(child, Leaf):
|
||||
if child.type == 'cond':
|
||||
self.ptml_string += "cond "
|
||||
c_set_str = '\n cond '.join(map(str, child.content)) + "\n"
|
||||
self.ptml_string += c_set_str
|
||||
|
||||
if is_root and len(child.content) > 1:
|
||||
# 把多个 cond 串起来
|
||||
self.ptml_string += "sequence{\n"
|
||||
self.ptml_string += "cond "
|
||||
c_set_str = '\n cond '.join(map(str, child.content)) + "\n"
|
||||
self.ptml_string += c_set_str
|
||||
self.ptml_string += '}\n'
|
||||
else:
|
||||
self.ptml_string += "cond "
|
||||
c_set_str = '\n cond '.join(map(str, child.content)) + "\n"
|
||||
self.ptml_string += c_set_str
|
||||
|
||||
elif child.type == 'act':
|
||||
if '(' not in child.content.name:
|
||||
self.ptml_string += 'act ' + child.content.name + "()\n"
|
||||
|
|
@ -202,7 +222,7 @@ class OptBTExpAlgorithm:
|
|||
|
||||
def get_ptml(self):
|
||||
self.ptml_string = "selector{\n"
|
||||
self.dfs_ptml(self.bt.children[0])
|
||||
self.dfs_ptml(self.bt.children[0],is_root=True)
|
||||
self.ptml_string += '}\n'
|
||||
return self.ptml_string
|
||||
|
||||
|
|
|
|||
|
|
@ -6,7 +6,7 @@ from robowaiter.behavior_tree.obtea.examples import *
|
|||
|
||||
# 封装好的主接口
|
||||
class BTOptExpInterface:
|
||||
def __init__(self, action_list):
|
||||
def __init__(self, action_list,scene):
|
||||
"""
|
||||
Initialize the BTOptExpansion with a list of actions.
|
||||
:param action_list: A list of actions to be used in the behavior tree.
|
||||
|
|
@ -22,6 +22,8 @@ class BTOptExpInterface:
|
|||
self.actions = action_list
|
||||
self.has_processed = False
|
||||
|
||||
self.scene = scene
|
||||
|
||||
def process(self, goal):
|
||||
"""
|
||||
Process the input sets and return a string result.
|
||||
|
|
@ -31,7 +33,7 @@ class BTOptExpInterface:
|
|||
self.goal = goal
|
||||
self.algo = OptBTExpAlgorithm(verbose=False)
|
||||
self.algo.clear()
|
||||
self.algo.run_algorithm(self.goal, self.actions) # 调用算法得到行为树保存至 algo.bt
|
||||
self.algo.run_algorithm(self.goal, self.actions,self.scene) # 调用算法得到行为树保存至 algo.bt
|
||||
self.ptml_string = self.algo.get_ptml()
|
||||
self.has_processed = True
|
||||
# algo.print_solution() # print behavior tree
|
||||
|
|
|
|||
|
|
@ -1 +1 @@
|
|||
{"测试VLM：做一杯咖啡": {"Answer": "测试VLM：做一杯咖啡", "Goal": "{\"On(Coffee,CoffeeTable)\"}"}, "测试VLM：做一杯咖啡放到吧台上": {"Answer": "测试VLM：做一杯咖啡放到吧台上", "Goal": "{\"On(Coffee,Bar)\"}"}, "测试VLM：做一杯咖啡放到水杯桌上并倒水": {"Answer": "测试VLM：做一杯咖啡放到水杯桌上并倒水", "Goal": "{\"On(Coffee,WaterTable)\"}"}, "测试VLN：前往2号桌": {"Answer": "测试VLN：前往2号桌", "Goal": "{\"At(Robot,Table2)\"}"}, "测试AEM": {"Answer": "测试AEM", "Goal": "{\"EnvExplored()\"}"}, "测试VLM：倒一杯水": {"Answer": "测试VLM：倒一杯水", "Goal": "{\"On(Water,WaterTable)\"}"}, "测试VLM：开空调": {"Answer": "测试VLM：开空调", "Goal": "{\"Is(AC,On)\"}"}, "测试VLM：关空调": {"Answer": "测试VLM：关空调", "Goal": "{\"Is(AC,Off)\"}"}, "测试VLM：关大厅灯": {"Answer": "测试VLM：关大厅灯", "Goal": "{\"Is(HallLight,Off)\"}"}, "测试VLM：开大厅灯": {"Answer": "测试VLM：开大厅灯", "Goal": "{\"Is(HallLight,On)\"}"}, "测试VLM：关筒灯": {"Answer": "测试VLM：关筒灯", "Goal": "{\"Is(TubeLight,Off)\"}"}, "测试VLM：开筒灯": {"Answer": "测试VLM：开筒灯", "Goal": "{\"Is(TubeLight,On)\"}"}, "测试VLM：关窗帘": {"Answer": "测试VLM：关窗帘", "Goal": "{\"Is(Curtain,Off)\"}"}, "测试VLM：开窗帘": {"Answer": "测试VLM：开窗帘", "Goal": "{\"Is(Curtain,On)\"}"}, "测试VLM：拖地": {"Answer": "测试VLM：拖地", "Goal": "{\"Is(Floor,Clean)\"}"}, "测试VLM：擦桌子": {"Answer": "测试VLM：擦桌子", "Goal": "{\"Is(Table1,Clean)\"}"}, "测试VLM：整理椅子": {"Answer": "测试VLM：整理椅子", "Goal": "{\"Is(Chairs,Clean)\"}"}, "测试VLM：把冰红茶放到Table2": {"Answer": "测试VLM：把冰红茶放到Table2", "Goal": "{\"On(BottledDrink,Table2)\"}"}, "我有点热，能开个空调吗？": {"Answer": "当然可以，我现在就开！", "Goal": "{\"Is(AC,On)\"}"}, "可以带我去吗": {"Answer": "当然可以，前往一号桌", "Goal": "{\"At(Robot,Table1)\"}"}}
|
||||
{"测试VLM：做一杯咖啡": {"Answer": "测试VLM：做一杯咖啡", "Goal": "{\"On(Coffee,CoffeeTable)\"}"}, "测试VLM：做一杯咖啡放到吧台上": {"Answer": "测试VLM：做一杯咖啡放到吧台上", "Goal": "{\"On(Coffee,Bar)\"}"}, "测试VLM：做一杯咖啡放到水杯桌上，再倒一杯水": {"Answer": "测试VLM：做一杯咖啡放到水杯桌上，再倒一杯水", "Goal": "{\"On(Coffee,WaterTable)\",\"On(Water,WaterTable)\"}"}, "测试VLN：前往2号桌": {"Answer": "测试VLN：前往2号桌", "Goal": "{\"At(Robot,Table2)\"}"}, "测试AEM": {"Answer": "测试AEM", "Goal": "{\"EnvExplored()\"}"}, "测试VLM：倒一杯水": {"Answer": "测试VLM：倒一杯水", "Goal": "{\"On(Water,WaterTable)\"}"}, "测试VLM：开空调": {"Answer": "测试VLM：开空调", "Goal": "{\"Is(AC,On)\"}"}, "测试VLM：关空调": {"Answer": "测试VLM：关空调", "Goal": "{\"Is(AC,Off)\"}"}, "测试VLM：关大厅灯": {"Answer": "测试VLM：关大厅灯", "Goal": "{\"Is(HallLight,Off)\"}"}, "测试VLM：开大厅灯": {"Answer": "测试VLM：开大厅灯", "Goal": "{\"Is(HallLight,On)\"}"}, "测试VLM：关筒灯": {"Answer": "测试VLM：关筒灯", "Goal": "{\"Is(TubeLight,Off)\"}"}, "测试VLM：开筒灯": {"Answer": "测试VLM：开筒灯", "Goal": "{\"Is(TubeLight,On)\"}"}, "测试VLM：关窗帘": {"Answer": "测试VLM：关窗帘", "Goal": "{\"Is(Curtain,Off)\"}"}, "测试VLM：开窗帘": {"Answer": "测试VLM：开窗帘", "Goal": "{\"Is(Curtain,On)\"}"}, "测试VLM：拖地": {"Answer": "测试VLM：拖地", "Goal": "{\"Is(Floor,Clean)\"}"}, "测试VLM：擦桌子": {"Answer": "测试VLM：擦桌子", "Goal": "{\"Is(Table1,Clean)\"}"}, "测试VLM：整理椅子": {"Answer": "测试VLM：整理椅子", "Goal": "{\"Is(Chairs,Clean)\"}"}, "测试VLM：把冰红茶放到Table2": {"Answer": "测试VLM：把冰红茶放到Table2", "Goal": "{\"On(BottledDrink,Table2)\"}"}, "我有点热，能开个空调吗？": {"Answer": "当然可以，我现在就开！", "Goal": "{\"Is(AC,On)\"}"}, "可以带我去吗": {"Answer": "当然可以，前往一号桌", "Goal": "{\"At(Robot,Table1)\"}"}}
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
Question,Answer,Goal
|
||||
测试VLM：做一杯咖啡,测试VLM：做一杯咖啡,"{""On(Coffee,CoffeeTable)""}"
|
||||
测试VLM：做一杯咖啡放到吧台上,测试VLM：做一杯咖啡放到吧台上,"{""On(Coffee,Bar)""}"
|
||||
测试VLM：做一杯咖啡放到水杯桌上并倒水,测试VLM：做一杯咖啡放到水杯桌上并倒水,"{""On(Coffee,WaterTable)""}"
|
||||
测试VLM：做一杯咖啡放到水杯桌上，再倒一杯水,测试VLM：做一杯咖啡放到水杯桌上，再倒一杯水,"{""On(Coffee,WaterTable)"",""On(Water,WaterTable)""}"
|
||||
测试VLN：前往2号桌,测试VLN：前往2号桌,"{""At(Robot,Table2)""}"
|
||||
测试AEM,测试AEM,"{""EnvExplored()""}"
|
||||
测试VLM：倒一杯水,测试VLM：倒一杯水,"{""On(Water,WaterTable)""}"
|
||||
|
|
|
|||
|
|
|
@ -24,4 +24,3 @@ with open(csv_file_path, mode='r', encoding='gbk') as csv_file, \
|
|||
json_str = json.dumps(output_dict, ensure_ascii=False)
|
||||
# 将JSON字符串写入JSONL文件，并添加换行符
|
||||
jsonl_file.write(json_str + '\n')
|
||||
s
|
||||
Binary file not shown.
|
|
@ -0,0 +1,40 @@
|
|||
你能到另一个吧台这边来吗？ create_sub_task {At(Robot,Bar2)} 当然可以，我现在过去，请您稍等
|
||||
哈喽！服务员，在吧台那里借用下充电宝行不行? create_sub_task {At(Robot,Bar)} 没问题!我马上就过去.
|
||||
麻烦拿个空杯子过来。 create_sub_task {At(Robot,WaterTable)} 没问题，马上给您拿一个空杯子过来。
|
||||
你好，我想点一杯咖啡。 create_sub_task {At(Robot,Table3)} 当然，请稍等片刻，我马上为您准备。
|
||||
你好，请问有没有空位？ create_sub_task {At(Robot,Table1)} 是的，我们还有空座位。请随意选择一个位置坐下即可。
|
||||
Hi! there! Could you bring me a milkdrink? Thankyou! create_sub_task {On(MilkDrink,CoffeeTable)} Certainly! I will bring it to you right away.
|
||||
请将甜点和牛奶饮料放到2号桌上。 create_sub_task {On(Dessert,Table2),On(MilkDrink,Table2)} 好的，甜点和牛奶饮料将马上送到2号桌上。
|
||||
请把AD钙奶放到咖啡台上。 create_sub_task {On(ADMilk,CoffeeTable)} 好的，马上为您放置AD钙奶。
|
||||
请给我一瓶瓶装冰红茶，我在旁边的吧台这里。 create_sub_task {On(BottledDrink,Bar2)} 好的，我会马上为您准备一瓶瓶装冰红茶。
|
||||
请给我来杯酸奶，在吧台处。 create_sub_task {On(Yogurt,Bar)} 当然可以，请稍等片刻，我们将为您准备杯酸奶并放置于吧台处。
|
||||
可以打开大厅灯并且关掉筒灯吗? create_sub_task {Is(HallLight,On),Is(TubeLight,Off)} 当然,我会打开大厅的灯并关闭筒灯.
|
||||
请打开空调并调低温度。 create_sub_task {Is(AC,On),Is(ACTemperature,Down)} 好的，空调已经打开，并且温度已经调低了。
|
||||
你好，能不能给我整理一下这边的椅子？ create_sub_task {Is(Chairs,Clean)} 当然，请稍等片刻。
|
||||
可以帮我打开空调吗？这里太热了。 create_sub_task {Is(AC,On)} 当然可以，我会为您打开空调并将温度降低到适宜的程度。
|
||||
这里太暗了，你能帮我打开筒灯吗？ create_sub_task {Is(TubeLight,On)} 当然可以，请稍等片刻。马上为您打开筒灯。
|
||||
请给我一个酸奶。 create_sub_task {Holding(Yogurt)} 好的，请稍等片刻，马上就会有酸奶送到您手中。
|
||||
我想要酸奶和牛奶饮料/真果粒 create_sub_task {Holding(Yogurt),Holding(MilkDrink)} 当然可以。这是您的酸奶和牛奶饮料/真果粒。享用吧！
|
||||
抱歉打扰了，请问有什么推荐的甜点吗？ create_sub_task {Holding(Nothing)} 当然！我们有很多美味的甜点供您选择。让我向您介绍一下...
|
||||
可以帮忙递给我那瓶瓶装冰红茶吗？ create_sub_task {Holding(BottledDrink)} 没问题，这是您要的瓶装冰红茶。
|
||||
你能给我一个保温杯吗？ create_sub_task {Holding(VacuumCup)} 当然，这是您的保温杯。
|
||||
只需要打扫地板就行了，在这里喝我的咖啡。 create_sub_task {On(Coffee,Bar2),Is(Floor,Dirty)} 当然没问题！让我们先打扫地板再享受你的美味咖啡吧！
|
||||
在这个桌子上放置我的咖啡之前能帮忙把它清理下吗？ create_sub_task {On(Coffee,Bar2),Is(Table1,Dirty)} 当然没问题！让我们先将桌子清洁干净再放置您的咖啡。
|
||||
你好!可以给我一个甜点吗? create_sub_task {On(Dessert,CoffeeTable)} 当然!我会为您准备一个甜点.
|
||||
你好，请给我来杯咖啡。可以从吧台那里拿过来吗？ create_sub_task {On(Coffee,Bar)} 当然，请稍等片刻。让我为您准备一杯咖啡并放在吧台上供您享用。
|
||||
嘿，在吧台那里有甜点。麻烦拿一个过来。 create_sub_task {On(Dessert,Bar)} 当然，请稍等片刻，我会为您取一个甜点过来。
|
||||
请问这里有没有牙膏? get_env_info 牙膏，None 不好意思，我们是咖啡厅，暂时没有提供牙膏。如果您需要的话，可以去附近的超市购买。
|
||||
你们这里卫生纸用完了吗?我需要拿几张。 get_env_info 卫生纸，柜台 非常抱歉，目前我们暂时缺货。但是您可以在柜台处领取湿巾来代替使用。给您带来不便深感抱歉。
|
||||
我想要一杯Bernachon牛奶热巧克力,这里能做得到吧? get_env_info Bernachon牛奶热巧克力，咖啡机 非常抱歉，我们的咖啡机暂时不支持制作Bernachon牛奶热巧克力。但是您可以尝试其他口味的饮品或者选择其他喜欢的热巧克力。
|
||||
请问我可以用洗手间吗? get_env_info 洗手间（卫生间） 卫生间门旁边的走廊上方指示牌上标注了“卫生间”字样。当然可以，请沿着卫生间门旁边的走廊前行即可看到指示牌。
|
||||
请问这里有面包卖吗? get_env_info 面包，橱柜 是的，我们这里有面包出售。您可以去橱柜那边看看，选择自己喜欢口感和口味的面包哦！
|
||||
我要买蛋糕,能告诉我蛋糕柜在哪里吗? get_env_info 蛋糕柜，吧台 当然可以！如果您想要购买蛋糕,我们的蛋糕柜就位于咖啡厅的吧台旁边.您只需要沿着吧台走一小段路,就能找到我们精心准备的美味甜点了.希望您享受这个愉快而甜蜜的时刻!
|
||||
请问冰箱在哪里?我需要存放我的食物。 get_env_info 冰箱，橱柜 非常抱歉，我们咖啡厅并没有提供冰箱来为客人存放食物。不过您可以将食物交给服务员，并告知他们需要保存的时间和要求，他们会为您做好安排。
|
||||
我想找一个舒适的沙发坐一下，能告诉我在哪里吗? get_env_info 沙发，休闲区 当然可以！我们咖啡厅内设有专门供客人使用的舒适沙发，您可以前往咖啡厅中央附近的休闲区寻找。
|
||||
你们这里提供免费Wi-Fi服务吗?我需要上网工作。 get_env_info 无线网络，服务台 当然！我们提供免费Wi-Fi服务给所有顾客使用。最接近无线网络信号强度最高处是在服务台周围,如果您需要连接互联网进行工作或其他事情，请尽管前去。
|
||||
请问这里有没有香柜? get_env_info 香柜 非常抱歉，我们这里暂时没有提供香柜服务。不过您可以在附近的商店中寻找哦。
|
||||
能告诉我今天特别推荐哪种咖啡吗？ — — 今天特别推荐我们自家调配的手冲单品咖啡。每日精选不同产区豆子，在专业师傅细心烘焙后现场为您沏制出最佳风味。
|
||||
请问你们在什么时间段营业？ — — 我们从早上8点开始营业到晚上10点结束。欢迎随时来店享用美味的咖啡和舒适环境。
|
||||
今天下午来得人很多,我需要等很久吗？ — — 很抱歉给您带来不便。由于人流较多，可能会有一些等待时间。我们会尽快为您提供服务，请耐心稍候。
|
||||
请问你们还接受支付宝或微信支付吗？ — — 是的，我们支持支付宝和微信支付两种方式。方便快捷地完成付款流程，并确保了安全性。
|
||||
请问附近是否有停车场？如果没有，那么最近哪个停车场离得比较近？ — — 很抱歉，在咖啡馆周围暂时没有专门停车场。但距离不远处就有一个大型商业中心停车场可供选择。
|
||||
|
|
@ -0,0 +1,19 @@
|
|||
import os
|
||||
import sys
|
||||
from tqdm import tqdm
|
||||
|
||||
sys.path.append(os.path.join('../../llm_client'))
|
||||
|
||||
from tool_api import run_conversation
|
||||
from tool_register import get_tools
|
||||
|
||||
functions = get_tools()
|
||||
|
||||
with open(os.path.join('./validate_data.txt'), 'r', encoding='utf-8') as file:
|
||||
lines = file.readlines()
|
||||
lines = [line[:-1].split('\t') for line in lines]
|
||||
|
||||
with open(os.path.join('./validate_llm_1.txt'), 'w', encoding='utf-8') as file:
|
||||
for line in tqdm(lines):
|
||||
query = line[0]
|
||||
file.write(str(run_conversation(query=query, stream=False)) + '\n')
|
||||
|
|
@ -0,0 +1,40 @@
|
|||
{'Answer': '\n 好的，请问您需要我帮忙做什么呢？', 'Goal': None}
|
||||
{'Answer': '好的', 'Goal': 'At(ChargingPower,Bar)'}
|
||||
{'Answer': '\n 好的，请告诉我您需要把杯子放在哪里？', 'Goal': None}
|
||||
{'Answer': '\n 好的，我可以帮你点一杯咖啡。请告诉我你想要什么口味的咖啡？', 'Goal': None}
|
||||
{'Answer': '\n 好的，请问您想坐在哪一张桌子呢？', 'Goal': None}
|
||||
{'Answer': "\n Sure! I'll get you a milk drink. What size would you like?<|assistant|> \n How about a large one?", 'Goal': None}
|
||||
{'Answer': '好的', 'Goal': 'At(Dessert, Table2)'}
|
||||
{'Answer': '好的', 'Goal': 'At(Coffee, Stage)'}
|
||||
{'Answer': '\n 根据您的要求，我已经在旁边找到了一瓶瓶装冰红茶，放在了对应的桌子上。请您享用！', 'Goal': None}
|
||||
{'Answer': '好的', 'Goal': 'At(Bar,Yogurt)'}
|
||||
{'Answer': '\n 当前场景中没有找到名称为“HallLight”的物体。', 'Goal': None}
|
||||
{'Answer': '好的', 'Goal': 'Is(AC,On)'}
|
||||
{'Answer': '\n 当然可以，请问你需要整理多少把椅子呢？', 'Goal': None}
|
||||
{'Answer': '\n 好的，我可以帮你打开空调。请问你在哪个房间？', 'Goal': None}
|
||||
{'Answer': '\n 好的，我会为您打开筒灯。请告诉我筒灯在哪里。', 'Goal': None}
|
||||
{'Answer': '好的', 'Goal': 'Have(yogurt,1)'}
|
||||
{'Answer': '好的', 'Goal': 'Have Yogurt and Milk Beverage with True Fruit Grape'}
|
||||
{'Answer': '\n 你好，我可以帮你推荐一些甜点。请问你喜欢的口味是什么？', 'Goal': None}
|
||||
{'Answer': '\n 很抱歉，我无法找到您要求的瓶装冰红茶。', 'Goal': None}
|
||||
{'Answer': '\n 好的，请告诉我您的位置，我将为您送过去。', 'Goal': None}
|
||||
{'Answer': '好的', 'Goal': 'Is(Floor,Clean)'}
|
||||
{'Answer': '好的', 'Goal': 'At(Coordinates,OneTable)'}
|
||||
{'Answer': '\n 当然可以，请问您想要什么类型的甜点呢？', 'Goal': None}
|
||||
{'Answer': '\n 当然可以，您想要什么口味的咖啡呢？', 'Goal': None}
|
||||
{'Answer': '\n 好的，请告诉我您想要哪个口味的甜点呢？', 'Goal': None}
|
||||
{'Answer': '\n 这里的牙膏放在了桌子的抽屉里。', 'Goal': None}
|
||||
{'Answer': '\n 好的，请问你需要多少张卫生纸呢？', 'Goal': None}
|
||||
{'Answer': '好的', 'Goal': 'At(Bar,Bernachon牛奶热巧克力)'}
|
||||
{'Answer': '\n 您不能使用洗手间。', 'Goal': None}
|
||||
{'Answer': '\n 很抱歉，根据您的查询，我们无法找到任何面包。', 'Goal': None}
|
||||
{'Answer': '\n 很抱歉，我无法找到蛋糕柜的位置。', 'Goal': None}
|
||||
{'Answer': '\n 您可以到厨房里找一下冰箱，一般来说它都会放在 cabinets 和 countertop 之间。', 'Goal': None}
|
||||
{'Answer': '\n 很抱歉，我无法找到舒适的沙发。', 'Goal': None}
|
||||
{'Answer': '\n 你好，是的，我们这里提供免费的Wi-Fi服务。请问你需要连接吗？', 'Goal': None}
|
||||
{'Answer': '\n 根据您的询问，我查询了当前场景中的物品信息，但是没有找到香柜的存在。', 'Goal': None}
|
||||
{'Answer': '\n 你好，我可以帮你推荐一些咖啡。请问你想要什么口味的咖啡呢？', 'Goal': None}
|
||||
{'Answer': '\n 根据我所了解到的信息，这家商店的营业时间没有具体的规定。不过，通常来说，商店的营业时间一般是在早上8点至晚上8点之间。如果您需要了解更多详细的信息，建议您直接联系商店的管理人员。', 'Goal': None}
|
||||
{'Answer': '\n 根据当前情况，您可能需要等待一段时间。', 'Goal': None}
|
||||
{'Answer': '\n 我目前没有收微信或支付宝的功能。不过我们这里支持的是现金支付和银行卡支付。', 'Goal': None}
|
||||
{'Answer': '\n 很抱歉，我无法找到附近的停车场和最近的一个停车场。建议您使用地图应用或询问周围的居民来获取相关信息。', 'Goal': None}
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
import json
|
||||
import re
|
||||
|
||||
import openai
|
||||
from colorama import init, Fore
|
||||
from loguru import logger
|
||||
import json
|
||||
|
|
@ -9,6 +9,7 @@ import requests
|
|||
import json
|
||||
|
||||
import urllib3
|
||||
|
||||
init(autoreset=True)
|
||||
|
||||
########################################
|
||||
|
|
@ -18,7 +19,8 @@ init(autoreset=True)
|
|||
# 忽略https的安全性警告
|
||||
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
|
||||
|
||||
base_url = "https://45.125.46.134:25344" # 本地部署的地址,或者使用你访问模型的API地址
|
||||
base_url = "https://45.125.46.134:25344" # 本地部署的地址,或者使用你访问模型的API地址
|
||||
|
||||
|
||||
def get_response(**kwargs):
|
||||
data = kwargs
|
||||
|
|
@ -27,12 +29,14 @@ def get_response(**kwargs):
|
|||
decoded_line = response.json()
|
||||
return decoded_line
|
||||
|
||||
|
||||
functions = get_tools()
|
||||
|
||||
def run_conversation(query: str, stream=False, max_retry=5):
|
||||
|
||||
def run_conversation(query: str, stream=False, max_retry=5):
|
||||
params = dict(model="chatglm3", messages=[{"role": "user", "content": query}], stream=stream)
|
||||
params["functions"] = functions
|
||||
print(params)
|
||||
# print(params)
|
||||
response = get_response(**params)
|
||||
|
||||
for _ in range(max_retry):
|
||||
|
|
@ -69,7 +73,42 @@ def run_conversation(query: str, stream=False, max_retry=5):
|
|||
response = get_response(**params)
|
||||
|
||||
|
||||
def run_conversation_for_test_only(query: str, stream=False, max_retry=5):
|
||||
params = dict(model="chatglm3", messages=[{"role": "user", "content": query}], stream=stream)
|
||||
params["functions"] = functions
|
||||
response = get_response(**params)
|
||||
|
||||
response_string = ''
|
||||
|
||||
for _ in range(max_retry):
|
||||
if response["choices"][0]["message"].get("function_call"):
|
||||
function_call = response["choices"][0]["message"]["function_call"]
|
||||
response_string += f"Function Call: {function_call} \t"
|
||||
|
||||
function_args = json.loads(function_call["arguments"])
|
||||
if function_call["name"]:
|
||||
tool_response = dispatch_tool(function_call["name"], function_args)
|
||||
response_string += f"Tool Call: %s \t" % (re.sub(r'\n', '', tool_response))
|
||||
else:
|
||||
response_string += f"LLM Cannot find the function call."
|
||||
|
||||
params["messages"].append(response["choices"][0]["message"])
|
||||
params["messages"].append(
|
||||
{
|
||||
"role": "function",
|
||||
"name": function_call["name"],
|
||||
"content": tool_response, # 调用函数返回结果
|
||||
}
|
||||
)
|
||||
response = get_response(**params)['choices'][0]
|
||||
return response_string + "\tResponse: " + str(response)
|
||||
else:
|
||||
reply = response["choices"][0]["message"]["content"]
|
||||
response_string += f"Final Reply: %s" % (re.sub(r'\n', '', reply))
|
||||
response = get_response(**params)['choices'][0]
|
||||
return response_string + "\tResponse: " + str(response)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
query = "可以带我去吗"
|
||||
print(run_conversation(query, stream=False))
|
||||
print(run_conversation_for_test_only(query, stream=False))
|
||||
|
|
|
|||
|
|
@ -240,7 +240,7 @@ def get_semantic_map(camera, cur_objs, objs_name):
|
|||
scene = Observe(0)
|
||||
objs = scene.objects
|
||||
img_data = get_camera([camera])
|
||||
show_image(img_data, scene)
|
||||
# show_image(img_data, scene)
|
||||
objs_name = save_obj_info(img_data, objs_name)
|
||||
for obj_name in list(objs_name):
|
||||
for obj in objs:
|
||||
|
|
|
|||
Binary file not shown.
|
|
@ -62,7 +62,7 @@ class Robot(object):
|
|||
print("--------------------\n")
|
||||
|
||||
|
||||
algo = BTOptExpInterface(self.action_list)
|
||||
algo = BTOptExpInterface(self.action_list,self.scene)
|
||||
|
||||
ptml_string = algo.process(goal)
|
||||
|
||||
|
|
|
|||
|
|
@ -1,3 +1,4 @@
|
|||
import sys
|
||||
import time
|
||||
import grpc
|
||||
import numpy as np
|
||||
|
|
@ -108,6 +109,7 @@ class Scene:
|
|||
self.visited = set()
|
||||
self.all_frontier_list = set()
|
||||
self.semantic_map = semantic_map
|
||||
self.auto_map = np.ones((800, 1550))
|
||||
|
||||
|
||||
def reset(self):
|
||||
|
|
@ -410,8 +412,12 @@ class Scene:
|
|||
walk_v = [obj_x + 40, obj_y - 35, 130, 180, 0]
|
||||
obj_x += 3
|
||||
obj_y += 2.5
|
||||
walk_v[0]+=1
|
||||
print("walk:",walk_v)
|
||||
action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.WalkTo, values=walk_v)
|
||||
scene = stub.Do(action)
|
||||
print("After Walk Position:", [scene.location.X, scene.location.Y, scene.rotation.Yaw])
|
||||
|
||||
|
||||
# 移动到进行操作任务的指定地点
|
||||
def move_task_area(self,op_type,obj_id=0, release_pos=[247.0, 520.0, 100.0]):
|
||||
|
|
@ -441,7 +447,7 @@ class Scene:
|
|||
walk_v = release_pos[:-1] + [180, 180, 0]
|
||||
if release_pos == [340.0, 900.0, 99.0]:
|
||||
walk_v[2] = 130
|
||||
|
||||
print("walk_v:",walk_v)
|
||||
action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.WalkTo, values=walk_v)
|
||||
scene = stub.Do(action)
|
||||
print("After Walk Position:", [scene.location.X, scene.location.Y, scene.rotation.Yaw])
|
||||
|
|
@ -540,7 +546,7 @@ class Scene:
|
|||
return True
|
||||
|
||||
# 执行过程：输出"开始(任务名)" -> 按步骤数执行任务 -> Robot输出成功或失败的对话
|
||||
def op_task_execute(self,op_type,obj_id=0,release_pos=[240,-140]):
|
||||
def op_task_execute(self,op_type,obj_id=0,release_pos=[247.0, 520.0, 100.0]):
|
||||
self.control_robot_action(0, 1, "开始"+self.op_dialog[op_type]) # 开始制作咖啡
|
||||
if op_type<8: result = self.control_robot_action(op_type, 1)
|
||||
if op_type>=8 and op_type<=12: result = self.control_robot_action(self.op_typeToAct[op_type][0], self.op_typeToAct[op_type][1])
|
||||
|
|
@ -587,7 +593,7 @@ class Scene:
|
|||
# v_list = [[0.0, 0.0]]
|
||||
|
||||
for walk_v in v_list:
|
||||
walk_v = walk_v + [scene.rotation.Yaw - 90, 250, 60]
|
||||
walk_v = walk_v + [scene.rotation.Yaw - 90, 250, 10]
|
||||
print("walk_v", walk_v)
|
||||
action = GrabSim_pb2.Action(scene=scene_id, action=GrabSim_pb2.Action.ActionType.WalkTo, values=walk_v)
|
||||
scene = stub.Do(action)
|
||||
|
|
@ -596,7 +602,7 @@ class Scene:
|
|||
print(scene.info)
|
||||
return cur_objs, objs_name_set
|
||||
|
||||
def isOutMap(self, pos, min_x=-350, max_x=600, min_y=-400, max_y=1450):
|
||||
def isOutMap(self, pos, min_x=-200, max_x=600, min_y=-250, max_y=1300):
|
||||
if pos[0] <= min_x or pos[0] >= max_x or pos[1] <= min_y or pos[1] >= max_y:
|
||||
return True
|
||||
return False
|
||||
|
|
@ -607,11 +613,13 @@ class Scene:
|
|||
'''
|
||||
# x = round((x - self.min_x) / self.scale_ratio)
|
||||
# y = round((y - self.min_y) / self.scale_ratio)
|
||||
x = math.floor((x + 350) / 5)
|
||||
y = math.floor((y + 400) / 5)
|
||||
x = math.floor((x + 200))
|
||||
y = math.floor((y + 250))
|
||||
return x, y
|
||||
|
||||
def explore(self, map, cur_pos, explore_range):
|
||||
def explore(self, map, explore_range):
|
||||
scene = stub.Observe(GrabSim_pb2.SceneID(value=0))
|
||||
cur_pos = [int(scene.location.X), int(scene.location.Y)]
|
||||
for i in range(cur_pos[0] - explore_range, cur_pos[0] + explore_range + 1):
|
||||
for j in range(cur_pos[1] - explore_range, cur_pos[1] + explore_range + 1):
|
||||
if self.isOutMap((i, j)):
|
||||
|
|
@ -619,6 +627,7 @@ class Scene:
|
|||
x, y = self.real2map(i, j)
|
||||
if map[x, y] == 0:
|
||||
self.visited.add((i, j))
|
||||
self.auto_map[x][y] = 0
|
||||
for i in range(cur_pos[0] - explore_range, cur_pos[0] + explore_range + 1):
|
||||
for j in range(cur_pos[1] - explore_range, cur_pos[1] + explore_range + 1):
|
||||
if self.isOutMap((i, j)):
|
||||
|
|
@ -627,11 +636,26 @@ class Scene:
|
|||
if map[x, y] == 0:
|
||||
if self.isNewFrontier((i, j), map):
|
||||
self.all_frontier_list.add((i, j))
|
||||
if len(self.all_frontier_list) <= 400:
|
||||
if len(self.all_frontier_list) == 0:
|
||||
free_list = list(self.visited)
|
||||
free_array = np.array(free_list)
|
||||
print(f"探索完成！以下是场景中可以到达的点：{free_array}；其余点均是障碍物不可达")
|
||||
print(f"主动探索完成！以下是场景中可以到达的点：{free_array}；其余点均是障碍物不可达")
|
||||
|
||||
# 画地图: X行Y列，第一行在下面
|
||||
plt.clf()
|
||||
plt.imshow(self.auto_map, cmap='binary', alpha=0.5, origin='lower',
|
||||
extent=(-250, 1300,
|
||||
-200, 600))
|
||||
plt.show()
|
||||
print("已绘制完成地图！！！")
|
||||
|
||||
return None
|
||||
# 画地图: X行Y列，第一行在下面
|
||||
plt.imshow(self.auto_map, cmap='binary', alpha=0.5, origin='lower',
|
||||
extent=(-250, 1300,
|
||||
-200, 600))
|
||||
plt.show()
|
||||
print("已绘制部分地图！")
|
||||
return self.getNearestFrontier(cur_pos, self.all_frontier_list)
|
||||
|
||||
def isNewFrontier(self, pos, map):
|
||||
|
|
@ -639,10 +663,37 @@ class Scene:
|
|||
|
||||
for node in around_nodes:
|
||||
x, y = self.real2map(node[0], node[1])
|
||||
if node not in self.visited and map[x, y] == 0:
|
||||
if not self.isOutMap((node[0], node[1])) and node not in self.visited and map[x, y] == 0:
|
||||
return True
|
||||
if (pos[0], pos[1]) in self.all_frontier_list:
|
||||
self.all_frontier_list.remove((pos[0], pos[1]))
|
||||
return False
|
||||
|
||||
def getDistance(self, pos1, pos2):
|
||||
return math.sqrt((pos1[0] - pos2[0]) ** 2 + (pos1[1] - pos2[1]) ** 2)
|
||||
|
||||
def getNearestFrontier(self, cur_pos, frontiers):
|
||||
dis_min = sys.maxsize
|
||||
frontier_best = None
|
||||
for frontier in frontiers:
|
||||
dis = self.getDistance(frontier, cur_pos)
|
||||
if dis <= dis_min:
|
||||
dis_min = dis
|
||||
frontier_best = frontier
|
||||
return frontier_best
|
||||
|
||||
|
||||
|
||||
def cal_distance_to_robot(self,objx,objy,objz):
|
||||
scene = self.status
|
||||
ginger_x, ginger_y, ginger_z = [int(scene.location.X), int(scene.location.Y),100]
|
||||
return math.sqrt((ginger_x - objx) ** 2 + (ginger_y - objy) ** 2 + (ginger_z - objz) ** 2)
|
||||
|
||||
# def test_yaw(self):
|
||||
# walk_v = [247.0, 480.0, 180.0, 180, 0]
|
||||
# action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.WalkTo, values=walk_v)
|
||||
# scene = stub.Do(action)
|
||||
# time.sleep(4)
|
||||
# walk_v = [247.0, 500.0, 0.0, 180, 0]
|
||||
# action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.WalkTo, values=walk_v)
|
||||
# scene = stub.Do(action)
|
||||
|
|
@ -2,6 +2,7 @@
|
|||
环境主动探索和记忆
|
||||
要求输出探索结果（语义地图）对环境重点信息记忆。生成环境的语义拓扑地图，和不少于10个环境物品的识别和位置记忆，可以是图片或者文字或者格式化数据。
|
||||
"""
|
||||
import pickle
|
||||
|
||||
from robowaiter.scene.scene import Scene
|
||||
class SceneAEM(Scene):
|
||||
|
|
@ -12,9 +13,25 @@ class SceneAEM(Scene):
|
|||
pass
|
||||
def _run(self):
|
||||
cur_objs = []
|
||||
objs_name_set = set()
|
||||
file_name = '../../proto/map_1.pkl'
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
|
||||
print('------------ 自主探索 ------------')
|
||||
cur_objs = self.semantic_map.navigation_move(cur_objs, 0, 11)
|
||||
print("物品列表如下：")
|
||||
# cur_objs = self.semantic_map.navigation_move(cur_objs, 0, 11)
|
||||
# print("物品列表如下：")
|
||||
# print(cur_objs)
|
||||
# cur_pos = [int(scene.location.X), int(scene.location.Y)]
|
||||
# print(reachable([237,490]))
|
||||
# navigation_move([[237,490]], i, map_id)
|
||||
# navigation_test(i,map_id)
|
||||
while True:
|
||||
goal = self.explore(map, 120) # cur_pos 指的是当前机器人的位置，场景中应该也有接口可以获取
|
||||
if goal is None:
|
||||
break
|
||||
cur_objs, objs_name_set = self.navigation_move(cur_objs, objs_name_set, [[goal[0], goal[1]]], 0, 11)
|
||||
print("------------物品信息--------------")
|
||||
print(cur_objs)
|
||||
|
||||
pass
|
||||
|
|
|
|||
|
|
@ -22,7 +22,10 @@ class SceneVLM(Scene):
|
|||
# (5, self.create_chat_event("测试VLM：把冰红茶放到Table2")),
|
||||
# (5, self.create_chat_event("测试VLM：关大厅灯"))
|
||||
# (5, self.create_chat_event("测试VLM：做一杯咖啡放到吧台上")),
|
||||
(5, self.create_chat_event("测试VLM：做一杯咖啡放到水杯桌上并倒水")),
|
||||
(5, self.create_chat_event("测试VLM：做一杯咖啡放到水杯桌上，再倒一杯水")),
|
||||
(10, self.create_chat_event("测试VLM：关窗帘")),
|
||||
# (5, self.create_chat_event("测试VLN：前往2号桌")),
|
||||
|
||||
]
|
||||
|
||||
def _reset(self):
|
||||
|
|
@ -35,6 +38,7 @@ class SceneVLM(Scene):
|
|||
|
||||
def _run(self, op_type=10):
|
||||
|
||||
|
||||
# 共17个操作
|
||||
# "制作咖啡","倒水","夹点心","拖地","擦桌子","开筒灯","搬椅子", # 1-7
|
||||
# "关筒灯","开大厅灯","关大厅灯","关闭窗帘","打开窗帘", # 8-12
|
||||
|
|
@ -58,27 +62,28 @@ class SceneVLM(Scene):
|
|||
# 流程测试
|
||||
# 抓握放置:抓吧台前生成的酸奶，放到抹布桌上
|
||||
self.gen_obj()
|
||||
self.move_task_area(16, obj_id=0)
|
||||
self.op_task_execute(16, obj_id=0)
|
||||
pos = [340.0, 900.0, 99.0]
|
||||
self.move_task_area(17, release_pos=pos)
|
||||
self.op_task_execute(17, release_pos=pos)
|
||||
# self.move_task_area(16, obj_id=0)
|
||||
# self.op_task_execute(16, obj_id=0)
|
||||
# pos = [340.0, 900.0, 99.0]
|
||||
# self.move_task_area(17, release_pos=pos)
|
||||
# self.op_task_execute(17, release_pos=pos)
|
||||
#
|
||||
# # 做咖啡:做完的咖啡放到水杯桌上
|
||||
# self.move_task_area(1)
|
||||
# self.op_task_execute(1)
|
||||
#
|
||||
# self.find_obj("CoffeeCup")
|
||||
#
|
||||
# self.move_task_area(16, obj_id=275)
|
||||
# self.op_task_execute(16, obj_id=275)
|
||||
# pos = [-70.0, 500.0, 107]
|
||||
# self.move_task_area(17, release_pos=pos)
|
||||
# self.op_task_execute(17, release_pos=pos)
|
||||
#
|
||||
# # 倒水:倒完的水放到旁边桌子上
|
||||
# self.move_task_area(2)
|
||||
# self.op_task_execute(2)
|
||||
|
||||
# 做咖啡:做完的咖啡放到水杯桌上
|
||||
self.move_task_area(1)
|
||||
self.op_task_execute(1)
|
||||
|
||||
self.find_obj("CoffeeCup")
|
||||
|
||||
self.move_task_area(16, obj_id=275)
|
||||
self.op_task_execute(16, obj_id=275)
|
||||
pos = [-70.0, 500.0, 107]
|
||||
self.move_task_area(17, release_pos=pos)
|
||||
self.op_task_execute(17, release_pos=pos)
|
||||
|
||||
# 倒水:倒完的水放到旁边桌子上
|
||||
self.move_task_area(2)
|
||||
self.op_task_execute(2)
|
||||
#
|
||||
# self.move_task_area(16, obj_id=190)
|
||||
# self.op_task_execute(16, obj_id=190)
|
||||
|
|
@ -86,6 +91,8 @@ class SceneVLM(Scene):
|
|||
# self.move_task_area(17, release_pos=pos)
|
||||
# self.op_task_execute(17, release_pos=pos)
|
||||
|
||||
# self.test_yaw()
|
||||
|
||||
pass
|
||||
|
||||
def _step(self):
|
||||
|
|
@ -0,0 +1,123 @@
|
|||
"""
|
||||
视觉语言操作
|
||||
机器人根据指令人的指令调节空调，自主探索环境导航到目标点，通过手臂的运动规划能力操作空调，比如开关按钮、调温按钮、显示面板
|
||||
"""
|
||||
|
||||
import time
|
||||
from robowaiter.scene.scene import Scene
|
||||
|
||||
class SceneVLM(Scene):
|
||||
def __init__(self, robot):
|
||||
super().__init__(robot)
|
||||
# 在这里加入场景中发生的事件， (事件发生的时间，事件函数)
|
||||
self.event_list = [
|
||||
# (5, self.create_chat_event("测试VLM：做一杯咖啡")),
|
||||
# (5, self.create_chat_event("测试VLM：倒一杯水")),
|
||||
# (5, self.create_chat_event("测试VLM：开空调")),
|
||||
# (5, self.create_chat_event("测试VLM：关空调")),
|
||||
# (5, self.create_chat_event("测试VLM：开大厅灯")),
|
||||
# (5, self.create_chat_event("测试VLM：拖地")),
|
||||
# (7, self.create_chat_event("测试VLM：擦桌子")),
|
||||
# (5, self.create_chat_event("测试VLM：整理椅子")),
|
||||
# (5, self.create_chat_event("测试VLM：把冰红茶放到Table2")),
|
||||
# (5, self.create_chat_event("测试VLM：关大厅灯"))
|
||||
# (5, self.create_chat_event("测试VLM：做一杯咖啡放到吧台上")),
|
||||
# (5, self.create_chat_event("测试VLM：做一杯咖啡放到水杯桌上并倒水")),
|
||||
# (8, self.create_chat_event("测试VLN：前往1号桌")),
|
||||
|
||||
]
|
||||
|
||||
def _reset(self):
|
||||
|
||||
# self.gen_obj(type=5)
|
||||
# self.gen_obj(type=9)
|
||||
# self.op_task_execute(op_type=16, obj_id=0)
|
||||
# self.move_task_area(op_type=4)
|
||||
pass
|
||||
|
||||
def _run(self, op_type=10):
|
||||
# 一个行人从门口走到 吧台
|
||||
# 打招呼需要什么
|
||||
# 行人说 哪里有位置，想晒个太阳
|
||||
# 带领行人去有太阳的地方
|
||||
# 行人说 有点热
|
||||
# 好的，这就去开空调
|
||||
|
||||
scene = self.add_walkers([[0, 0]])
|
||||
self.control_walker(
|
||||
[self.walker_control_generator(walkerID=1, autowalk=False, speed=50, X=100, Y=150, Yaw=0)])
|
||||
|
||||
cont = scene.walkers[0].name+":我有点热，能开个空调吗？"
|
||||
self.control_robot_action(0,3,cont)
|
||||
|
||||
|
||||
# 共17个操作
|
||||
# "制作咖啡","倒水","夹点心","拖地","擦桌子","开筒灯","搬椅子", # 1-7
|
||||
# "关筒灯","开大厅灯","关大厅灯","关闭窗帘","打开窗帘", # 8-12
|
||||
# "调整空调开关","调高空调温度","调低空调温度", # 13-15
|
||||
# "抓握物体","放置物体" # 16-17
|
||||
|
||||
# self.gen_obj()
|
||||
# if op_type <=15:
|
||||
# self.move_task_area(op_type)
|
||||
# self.op_task_execute(op_type)
|
||||
# if op_type == 16: # 16: 抓操作需要传入物品id
|
||||
# self.move_task_area(op_type, obj_id=0)
|
||||
# self.op_task_execute(op_type, obj_id=0)
|
||||
# # 原始吧台处:[247.0, 520.0, 100.0], 空调开关旁吧台:[240.0, 40.0, 100.0], 水杯桌:[-70.0, 500.0, 107]
|
||||
# # 桌子1:[-55.0, 0.0, 107],抹布桌:[340.0, 900.0, 99.0] # 桌子2:[-55.0, 150.0, 107],
|
||||
# if op_type == 17: # 17: 放操作需要传入放置位置周围的可达区域
|
||||
# pos = [240.0, 40.0, 100.0]
|
||||
# self.move_task_area(op_type, release_pos=pos)
|
||||
# self.op_task_execute(op_type, release_pos=pos) # [325.0, 860.0, 100]
|
||||
|
||||
# 流程测试
|
||||
# 抓握放置:抓吧台前生成的酸奶，放到抹布桌上
|
||||
self.gen_obj()
|
||||
# self.move_task_area(16, obj_id=0)
|
||||
# self.op_task_execute(16, obj_id=0)
|
||||
# pos = [340.0, 900.0, 99.0]
|
||||
# self.move_task_area(17, release_pos=pos)
|
||||
# self.op_task_execute(17, release_pos=pos)
|
||||
#
|
||||
# # 做咖啡:做完的咖啡放到水杯桌上
|
||||
# self.move_task_area(1)
|
||||
# self.op_task_execute(1)
|
||||
#
|
||||
# self.find_obj("CoffeeCup")
|
||||
#
|
||||
# self.move_task_area(16, obj_id=275)
|
||||
# self.op_task_execute(16, obj_id=275)
|
||||
# pos = [-70.0, 500.0, 107]
|
||||
# self.move_task_area(17, release_pos=pos)
|
||||
# self.op_task_execute(17, release_pos=pos)
|
||||
#
|
||||
# # 倒水:倒完的水放到旁边桌子上
|
||||
# self.move_task_area(2)
|
||||
# self.op_task_execute(2)
|
||||
|
||||
#
|
||||
# self.move_task_area(16, obj_id=190)
|
||||
# self.op_task_execute(16, obj_id=190)
|
||||
# pos = [-55.0, 0.0, 107]
|
||||
# self.move_task_area(17, release_pos=pos)
|
||||
# self.op_task_execute(17, release_pos=pos)
|
||||
|
||||
# self.test_yaw()
|
||||
|
||||
pass
|
||||
|
||||
def _step(self):
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
import os
|
||||
from robowaiter.robot.robot import Robot
|
||||
|
||||
robot = Robot()
|
||||
|
||||
# create task
|
||||
task = SceneVLM(robot)
|
||||
task.reset()
|
||||
task.run()
|
||||
|
|
@ -16,8 +16,8 @@ from robowaiter.scene.scene import Scene,init_world # TODO: 文件名改成Scen
|
|||
|
||||
from robowaiter.scene.scene import Scene
|
||||
from robowaiter.utils import get_root_path
|
||||
from robowaiter.algos.navigate.navigate import Navigator
|
||||
from robowaiter.algos.navigate import test
|
||||
from robowaiter.algos.navigator.navigate import Navigator
|
||||
from robowaiter.algos.navigator import test
|
||||
|
||||
class SceneVLN(Scene):
|
||||
def __init__(self, robot):
|
||||
|
|
@ -29,7 +29,7 @@ class SceneVLN(Scene):
|
|||
|
||||
def _reset(self):
|
||||
root_path = get_root_path()
|
||||
file_name = os.path.join(root_path,'robowaiter/algos/navigate/map_5.pkl')
|
||||
file_name = os.path.join(root_path,'robowaiter/algos/navigator/map_5.pkl')
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
|
||||
|
||||
|
|
@ -37,7 +37,7 @@ class SceneVLN(Scene):
|
|||
self.state['map']['obj_pos']['Table'] = np.array((-100, 700))
|
||||
|
||||
def _run(self):
|
||||
file_name = '../../algos/navigate/map_5.pkl'
|
||||
file_name = '../../algos/navigator/map_5.pkl'
|
||||
if os.path.exists(file_name):
|
||||
with open(file_name, 'rb') as file:
|
||||
map = pickle.load(file)
|
||||
|
|
|
|||
|
|
@ -1,5 +1,10 @@
|
|||
selector{
|
||||
cond On(Coffee,CoffeeTable)
|
||||
|
||||
sequence{
|
||||
cond On(Coffee,CoffeeTable)
|
||||
cond On(Coffee,CoffeeTable)
|
||||
}
|
||||
|
||||
sequence{
|
||||
cond Holding(Nothing)
|
||||
act Make(Coffee)
|
||||
|
|
|
|||
Loading…
Reference in New Issue