79 lines
2.6 KiB
Python
79 lines
2.6 KiB
Python
|
import numpy as np
|
||
|
|
|
||
|
|
from xarm import Base
|
||
|
|
|
||
|
|
|
||
|
|
class Push(Base):
|
||
|
|
def __init__(self):
|
||
|
|
super().__init__("push")
|
||
|
|
|
||
|
|
def _reset_sim(self):
|
||
|
|
self._act_magnitude = 0
|
||
|
|
super()._reset_sim()
|
||
|
|
|
||
|
|
def is_success(self):
|
||
|
|
return np.linalg.norm(self.obj - self.goal) <= 0.05
|
||
|
|
|
||
|
|
def get_reward(self):
|
||
|
|
dist = np.linalg.norm(self.obj - self.goal)
|
||
|
|
penalty = self._act_magnitude**2
|
||
|
|
return -(dist + 0.15 * penalty)
|
||
|
|
|
||
|
|
def _get_obs(self):
|
||
|
|
eef_velp = self.sim.data.get_site_xvelp("grasp") * self.dt
|
||
|
|
gripper_angle = self.sim.data.get_joint_qpos("right_outer_knuckle_joint")
|
||
|
|
eef, goal = self.eef - self.center_of_table, self.goal - self.center_of_table
|
||
|
|
|
||
|
|
obj = self.obj - self.center_of_table
|
||
|
|
obj_rot = self.sim.data.get_joint_qpos("object_joint0")[-4:]
|
||
|
|
obj_velp = self.sim.data.get_site_xvelp("object_site") * self.dt
|
||
|
|
obj_velr = self.sim.data.get_site_xvelr("object_site") * self.dt
|
||
|
|
|
||
|
|
obs = np.concatenate(
|
||
|
|
[
|
||
|
|
eef,
|
||
|
|
eef_velp,
|
||
|
|
goal,
|
||
|
|
obj,
|
||
|
|
obj_rot,
|
||
|
|
obj_velp,
|
||
|
|
obj_velr,
|
||
|
|
eef - goal,
|
||
|
|
eef - obj,
|
||
|
|
obj - goal,
|
||
|
|
np.array(
|
||
|
|
[
|
||
|
|
np.linalg.norm(eef - goal),
|
||
|
|
np.linalg.norm(eef - obj),
|
||
|
|
np.linalg.norm(obj - goal),
|
||
|
|
gripper_angle,
|
||
|
|
]
|
||
|
|
),
|
||
|
|
],
|
||
|
|
axis=0,
|
||
|
|
)
|
||
|
|
return {"observation": obs, "state": eef, "achieved_goal": eef, "desired_goal": goal}
|
||
|
|
|
||
|
|
def _sample_goal(self):
|
||
|
|
# Gripper
|
||
|
|
gripper_pos = np.array([1.280, 0.295, 0.735]) + self.np_random.uniform(-0.05, 0.05, size=3)
|
||
|
|
super()._set_gripper(gripper_pos, self.gripper_rotation)
|
||
|
|
|
||
|
|
# Object
|
||
|
|
object_pos = self.center_of_table - np.array([0.25, 0, 0.07])
|
||
|
|
object_pos[0] += self.np_random.uniform(-0.08, 0.08, size=1)
|
||
|
|
object_pos[1] += self.np_random.uniform(-0.08, 0.08, size=1)
|
||
|
|
object_qpos = self.sim.data.get_joint_qpos("object_joint0")
|
||
|
|
object_qpos[:3] = object_pos
|
||
|
|
self.sim.data.set_joint_qpos("object_joint0", object_qpos)
|
||
|
|
|
||
|
|
# Goal
|
||
|
|
self.goal = np.array([1.600, 0.200, 0.545])
|
||
|
|
self.goal[:2] += self.np_random.uniform(-0.1, 0.1, size=2)
|
||
|
|
self.sim.model.site_pos[self.sim.model.site_name2id("target0")] = self.goal
|
||
|
|
return self.goal
|
||
|
|
|
||
|
|
def step(self, action):
|
||
|
|
self._act_magnitude = np.linalg.norm(action[:3])
|
||
|
|
return super().step(action)
|