diff --git a/robowaiter/behavior_lib/_base/Behavior.py b/robowaiter/behavior_lib/_base/Behavior.py index e23ab17..d070cba 100644 --- a/robowaiter/behavior_lib/_base/Behavior.py +++ b/robowaiter/behavior_lib/_base/Behavior.py @@ -30,6 +30,17 @@ class Bahavior(ptree.behaviour.Behaviour): # all_object = set() # all_place=set() + num_of_obj_on_place={ + 'Bar': 0, # (247.0, 520.0, 100.0) + 'Bar2': 0, + 'WaterTable': 0, + 'CoffeeTable': 0, + 'Table1': 0, + 'Table2': 0, + 'Table3': 0, + 'BrightTable6': 0, + } + place_xyz_dic={ 'Bar': (247.0, 520.0, 100.0), #(247.0, 520.0, 100.0) 'Bar2': (240.0, 40.0, 100.0), diff --git a/robowaiter/behavior_lib/act/Clean.py b/robowaiter/behavior_lib/act/Clean.py index bb9e9b3..714cce8 100644 --- a/robowaiter/behavior_lib/act/Clean.py +++ b/robowaiter/behavior_lib/act/Clean.py @@ -44,6 +44,7 @@ class Clean(Act): self.scene.state["condition_set"] |= (self.info["add"]) self.scene.state["condition_set"] -= self.info["del_set"] + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) # print("After Clean condition_set:",self.scene.state["condition_set"] ) return Status.RUNNING \ No newline at end of file diff --git a/robowaiter/behavior_lib/act/Make.py b/robowaiter/behavior_lib/act/Make.py index 32dd194..073ea06 100644 --- a/robowaiter/behavior_lib/act/Make.py +++ b/robowaiter/behavior_lib/act/Make.py @@ -54,6 +54,8 @@ class Make(Act): # 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) + if self.scene.take_picture: + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) self.scene.state["condition_set"] |= (self.info["add"]) self.scene.state["condition_set"] -= self.info["del_set"] diff --git a/robowaiter/behavior_lib/act/MoveTo.py b/robowaiter/behavior_lib/act/MoveTo.py index 2e8c73e..1f79829 100644 --- a/robowaiter/behavior_lib/act/MoveTo.py +++ b/robowaiter/behavior_lib/act/MoveTo.py @@ -32,6 +32,9 @@ class MoveTo(Act): # goal = self.scene.state['map']['obj_pos'][self.args[0]] # navigator.navigate_old(goal, animation=False) + if self.scene.take_picture: + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) + # 走到固定的地点 if self.target_place in Act.place_xy_yaw_dic: goal = Act.place_xy_yaw_dic[self.target_place] @@ -87,10 +90,12 @@ class MoveTo(Act): # print("MoveTo",obj_x, obj_y, obj_z," obj_id:",obj_id," obj_info:",obj_info.name) + if self.scene.take_picture: + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) + # goal = self.scene.state['map']['obj_pos'][self.args[0]] # self.scene.walk_to(goal[0],goal[1]) # X, Y, Yaw=None, velocity=200, dis_limit=0 - self.scene.state["condition_set"] |= (self.info["add"]) self.scene.state["condition_set"] -= self.info["del_set"] return ptree.common.Status.RUNNING diff --git a/robowaiter/behavior_lib/act/PickUp.py b/robowaiter/behavior_lib/act/PickUp.py index 83b1fe0..fafd7c8 100644 --- a/robowaiter/behavior_lib/act/PickUp.py +++ b/robowaiter/behavior_lib/act/PickUp.py @@ -56,6 +56,9 @@ class PickUp(Act): self.scene.move_task_area(op_type=16, obj_id=obj_id) self.scene.op_task_execute(op_type=16, obj_id=obj_id) + if self.scene.take_picture: + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) + self.scene.state["condition_set"] |= (self.info["add"]) self.scene.state["condition_set"] -= self.info["del_set"] return Status.RUNNING diff --git a/robowaiter/behavior_lib/act/PutDown.py b/robowaiter/behavior_lib/act/PutDown.py index d9a5770..5ca4479 100644 --- a/robowaiter/behavior_lib/act/PutDown.py +++ b/robowaiter/behavior_lib/act/PutDown.py @@ -33,8 +33,16 @@ 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] + + if Act.num_of_obj_on_place[self.target_place]>=1: + release_pos[1] += 25 + + Act.num_of_obj_on_place[self.target_place]+=1 + self.scene.move_task_area(op_type, release_pos=release_pos) self.scene.op_task_execute(op_type, release_pos=release_pos) + if self.scene.take_picture: + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) self.scene.state["condition_set"] |= (self.info["add"]) self.scene.state["condition_set"] -= self.info["del_set"] diff --git a/robowaiter/behavior_lib/act/Turn.py b/robowaiter/behavior_lib/act/Turn.py index cc14882..538d549 100644 --- a/robowaiter/behavior_lib/act/Turn.py +++ b/robowaiter/behavior_lib/act/Turn.py @@ -61,13 +61,13 @@ class Turn(Act): info["add"] = {f'Is({arg[0]},Off)'} info["del_set"] = {f'Is({arg[0]},On)'} elif arg[0]=='ACTemperature': - info["pre"] = {f'Holding(Nothing)'} + info["pre"] = {f'Holding(Nothing)',f'Is(AC,On)'} if arg[1]=="Up": - info["pre"] |= {f'Is({arg[0]},Down)'} + # info["pre"] |= {f'Is({arg[0]},Down)'} info["add"] = {f'Is({arg[0]},Up)'} info["del_set"] = {f'Is({arg[0]},Down)'} elif arg[1]=="Down": - info["pre"] |= {f'Is({arg[0]},Up)'} + # info["pre"] |= {f'Is({arg[0]},Up)'} info["add"] = {f'Is({arg[0]},Down)'} info["del_set"] = {f'Is({arg[0]},Up)'} return info @@ -76,7 +76,8 @@ class Turn(Act): self.scene.move_task_area(self.op_type) self.scene.op_task_execute(self.op_type) - + if self.scene.take_picture: + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) self.scene.state["condition_set"] |= (self.info["add"]) self.scene.state["condition_set"] -= self.info["del_set"] diff --git a/robowaiter/behavior_lib/cond/At.py b/robowaiter/behavior_lib/cond/At.py index a217217..ad0b92c 100644 --- a/robowaiter/behavior_lib/cond/At.py +++ b/robowaiter/behavior_lib/cond/At.py @@ -18,6 +18,8 @@ class At(Cond): def _update(self) -> ptree.common.Status: # if self.scene.status? + # self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) + if self.name in self.scene.state["condition_set"]: return ptree.common.Status.SUCCESS else: diff --git a/robowaiter/behavior_lib/cond/FocusingCustomer.py b/robowaiter/behavior_lib/cond/FocusingCustomer.py index 6e90329..1685a85 100644 --- a/robowaiter/behavior_lib/cond/FocusingCustomer.py +++ b/robowaiter/behavior_lib/cond/FocusingCustomer.py @@ -11,6 +11,8 @@ class FocusingCustomer(Cond): def _update(self) -> ptree.common.Status: # if self.scene.status? if "customer" in self.scene.state['attention']: + if self.scene.take_picture: + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) return ptree.common.Status.SUCCESS else: goal = Cond.place_xy_yaw_dic['Bar'] diff --git a/robowaiter/behavior_lib/cond/Holding.py b/robowaiter/behavior_lib/cond/Holding.py index 0e6a8d4..b756d4f 100644 --- a/robowaiter/behavior_lib/cond/Holding.py +++ b/robowaiter/behavior_lib/cond/Holding.py @@ -14,6 +14,8 @@ class Holding(Cond): def _update(self) -> ptree.common.Status: # if self.scene.status? + # self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) + if self.name in self.scene.state["condition_set"]: return ptree.common.Status.SUCCESS else: diff --git a/robowaiter/behavior_lib/cond/Is.py b/robowaiter/behavior_lib/cond/Is.py index 1f95a6d..1c7cfaa 100644 --- a/robowaiter/behavior_lib/cond/Is.py +++ b/robowaiter/behavior_lib/cond/Is.py @@ -24,6 +24,7 @@ class Is(Cond): def _update(self) -> ptree.common.Status: # if self.scene.status? + # self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) if self.name in self.scene.state["condition_set"]: return ptree.common.Status.SUCCESS diff --git a/robowaiter/behavior_lib/cond/NewCustomer.py b/robowaiter/behavior_lib/cond/NewCustomer.py index b72e026..8d46ca6 100644 --- a/robowaiter/behavior_lib/cond/NewCustomer.py +++ b/robowaiter/behavior_lib/cond/NewCustomer.py @@ -14,6 +14,8 @@ class NewCustomer(Cond): def _update(self) -> ptree.common.Status: + if self.scene.take_picture: + self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) # 获取customer的位置 # bar (247.0, 520.0, 100.0) close_to_bar = False diff --git a/robowaiter/behavior_lib/cond/On.py b/robowaiter/behavior_lib/cond/On.py index b2a6040..a299911 100644 --- a/robowaiter/behavior_lib/cond/On.py +++ b/robowaiter/behavior_lib/cond/On.py @@ -18,6 +18,7 @@ class On(Cond): # print("self.name:",self.name) # print("On: condition_set:",self.scene.state["condition_set"]) + # self.scene.get_obstacle_point(self.scene.db, self.status, map_ratio=self.scene.map_ratio) if self.name in self.scene.state["condition_set"]: return ptree.common.Status.SUCCESS diff --git a/robowaiter/llm_client/data/fix_questions.txt b/robowaiter/llm_client/data/fix_questions.txt index 63b7ce4..d6aa028 100644 --- a/robowaiter/llm_client/data/fix_questions.txt +++ b/robowaiter/llm_client/data/fix_questions.txt @@ -6,7 +6,7 @@ create_sub_task {"goal":"On(Coffee,CoffeeTable)"}00 -不用了 +不用了。 好的，您有需要再跟我说 stop_serve {} @@ -91,8 +91,26 @@ create_sub_task {"goal":"Is(AC,On),Is(Curtain,Off)"} +下班啦！别忘了打扫卫生。 +收到！请问您需要来点什么吗？ +create_sub_task +"{""Is(Floor,Clean)"",""Is(Table1,Clean)"",""Is(Chairs,Clean)"",""Is(AC,Off)"",""Is(HallLight,Off)"",""Is(TubeLight,Off)"",""Is(Curtain,Off)""}" + 请问洗手间在哪里？ 洗手间在这附近 get_object_info {"obj":"洗手间"} + + + +给我来杯酸奶和冰红茶，我坐在对面的桌子那儿。 +好的，请稍等。 +create_sub_task +{"goal":"On(BottledDrink,WaterTable),On(Yogurt,WaterTable)"} + + +好热呀，想开空调，想要温度调低点！ +抱歉，我马上去开空调并调低空调温度。 +create_sub_task +{"goal":"Is(ACTemperature,Down)"} diff --git a/robowaiter/proto/camera.py b/robowaiter/proto/camera.py index c310598..7400390 100644 --- a/robowaiter/proto/camera.py +++ b/robowaiter/proto/camera.py @@ -29,7 +29,7 @@ objects_dic = {} obstacle_objs_id = [114, 115, 122, 96, 102, 83, 121, 105, 108, 89, 100, 90, 111, 103, 95, 92, 76, 113, 101, 29, 112, 87, 109, 98, 106, 120, 97, 86, 104, 78, 85, 81, 82, 84, 91, 93, 94, - 99, 107, 116, 117, 118, 119, 255] + 99, 107, 116, 117, 118, 119, 255, 251] not_key_objs_id = {255,254,253,107,81} ''' @@ -367,12 +367,11 @@ def get_id_object_pixels(id, scene): world_points.append(transform_co(img_data_depth, pixel[0], pixel[1], d_depth[pixel[0]][pixel[1]][0], scene)) return world_points - - - -def get_obstacle_point(db, scene, cur_obstacle_world_points, map_ratio): +def get_obstacle_point(plt, db, scene, cur_obstacle_world_points, map_ratio): cur_obstacle_pixel_points = [] object_pixels = {} + obj_detect_count = 0 + cur_objs_id = [] colors = [ 'red', 'pink', @@ -403,10 +402,13 @@ def get_obstacle_point(db, scene, cur_obstacle_world_points, map_ratio): for item in items: key, value = item.split(":") objs_id[int(key)] = value + objs_id[251] = "walker" # plt.imshow(d_depth, cmap="gray" if "depth" in im_depth.name.lower() else None) # plt.show() - # - # plt.imshow(d_segment, cmap="gray" if "depth" in im_segment.name.lower() else None) + plt.subplot(2, 2, 1) + plt.imshow(d_segment, cmap="gray" if "depth" in im_segment.name.lower() else None) + plt.axis("off") + plt.title("相机分割") # plt.show() d_depth = np.transpose(d_depth, (1, 0, 2)) @@ -439,16 +441,21 @@ def get_obstacle_point(db, scene, cur_obstacle_world_points, map_ratio): world_point = transform_co(img_data_depth, pixel[0], pixel[1], d_depth[pixel[0]][pixel[1]][0], scene) cur_obstacle_world_points.append([world_point[0], world_point[1]]) # print(f"{pixel}：{[world_point[0], world_point[1]]}") - + plt.subplot(2, 2, 2) plt.imshow(d_color, cmap="gray" if "depth" in im_depth.name.lower() else None) + plt.axis('off') + plt.title("目标检测") + # plt.tight_layout() for key, value in object_pixels.items(): - if key == 101 or key == 0: + if key == 0 or key not in objs_id.keys(): continue - if key in [91, 84]: + + if key in [91, 84, 96, 87, 102, 106, 120, 85,113, 101, 83, 251]: X = np.array(value) db.fit(X) labels = db.labels_ + # 将数据按照聚类标签分组，并打印每个分组的数据 for i in range(max(labels) + 1): # 从0到最大聚类标签的值 group_data = X[labels == i] # 获取当前标签的数据 @@ -458,6 +465,9 @@ def get_obstacle_point(db, scene, cur_obstacle_world_points, map_ratio): y_min = min(p[1] for p in group_data) if x_max - x_min < 10 or y_max - y_min < 10: continue + if key != 251: + obj_detect_count += 1 + cur_objs_id.append(objs_id[key]) # 在指定的位置绘制方框 # 创建矩形框 rect = patches.Rectangle((x_min, y_min), (x_max - x_min), (y_max - y_min), linewidth=1, edgecolor=colors[key % 10], @@ -465,7 +475,11 @@ def get_obstacle_point(db, scene, cur_obstacle_world_points, map_ratio): plt.text(x_min, y_min, f'{objs_id[key]}', fontdict={'family': 'serif', 'size': 10, 'color': 'green'}, ha='center', va='center') plt.gca().add_patch(rect) + else: + if key != 251: + obj_detect_count += 1 + cur_objs_id.append(objs_id[key]) x_max = max(p[0] for p in value) y_max = max(p[1] for p in value) x_min = min(p[0] for p in value) @@ -484,11 +498,12 @@ def get_obstacle_point(db, scene, cur_obstacle_world_points, map_ratio): # rect = patches.Rectangle((0, 255), 15, 30, linewidth=1, edgecolor='g', # facecolor='none') + plt.subplot(2, 7, 14) # 这里的2,1表示总共2行，1列，2表示这个位置是第2个子图 - # 将矩形框添加到图像中 - # plt.gca().add_patch(rect) - plt.show() - return cur_obstacle_world_points + plt.text(0, 0.7, f'检测物体数量：{obj_detect_count}', fontsize=10) + + # plt.show() + return cur_obstacle_world_points, cur_objs_id diff --git a/robowaiter/proto/objs.json b/robowaiter/proto/objs.json index b6387ab..8f4779f 100644 --- a/robowaiter/proto/objs.json +++ b/robowaiter/proto/objs.json @@ -1 +1 @@ -[{"id": "0", "name": "Desk", "location": "Y: -6.000000212225132e-06\nZ: 144.0\n", "height": "288.0"}, {"id": "1", "name": "SaoBa", "location": "X: -180.0\nY: 720.0\n", "height": "0.0"}, {"id": "2", "name": "Broom", "location": "X: -120.0\nY: 770.0\n", "height": "0.0"}, {"id": "3", "name": "BoJi", "location": "X: -160.0\nY: 740.0\n", "height": "0.0"}, {"id": "4", "name": "XiGuan", "location": "X: 146.0\nY: 445.0\nZ: 90.69999694824219\n", "height": "181.39999389648438"}, {"id": "5", "name": "Sugar", "location": "X: 361.0\nY: 743.0\nZ: 90.5\n", "height": "181.0"}, {"id": "6", "name": "Sofa", "location": "X: 1.2000000424450263e-05\nY: -6.000000212225132e-06\nZ: 144.0\n", "height": "288.0"}, {"id": "7", "name": "XiangGui", "location": "X: 1.2000000424450263e-05\nY: -6.000000212225132e-06\nZ: 144.0\n", "height": "288.0"}, {"id": "8", "name": "BaTai", "location": "X: 1.2000000424450263e-05\nY: -6.000000212225132e-06\nZ: 144.0\n", "height": "288.0"}, {"id": "9", "name": "Chair", "location": "X: -159.99998474121094\nY: 72.99999237060547\nZ: 40.0\n", "height": "80.0"}, {"id": "10", "name": "CoffeeCup", "location": "X: 150.0\nY: 471.0\nZ: 84.0\n", "height": "168.0"}, {"id": "11", "name": "TuoBu", "location": "X: -200.0\nY: 685.0\nZ: 3.5\n", "height": "7.0"}, {"id": "12", "name": "Box", "location": "X: 132.0\nY: 445.0\nZ: 89.0\n", "height": "178.0"}, {"id": "13", "name": "TuoPan", "location": "X: 179.0\nY: 470.0\nZ: 95.0\n", "height": "190.0"}, {"id": "14", "name": "WaterCup", "location": "X: 400.0\nY: 829.0999755859375\nZ: 96.0\n", "height": "192.0"}, {"id": "15", "name": "Kettle", "location": "X: -137.76065063476562\nY: 436.5726318359375\nZ: 89.0\n", "height": "178.0"}, {"id": "16", "name": "Spoon", "location": "X: 132.5\nY: 446.0\nZ: 90.0\n", "height": "180.0"}, {"id": "17", "name": "ZhiBeiHe", "location": "X: 152.0\nY: 292.0\nZ: 96.0\n", "height": "192.0"}, {"id": "18", "name": "ZhuZi", "location": "X: 1.2000000424450263e-05\nY: -6.000000212225132e-06\nZ: 144.0\n", "height": "288.0"}, {"id": "19", "name": "Desk", "location": "Z: 148.0\n", "height": "296.0"}, {"id": "20", "name": "Door", "location": "X: 1.2000000424450263e-05\nY: -6.000000212225132e-06\nZ: 144.0\n", "height": "288.0"}, {"id": "21", "name": "XiGuan", "location": "X: 146.0\nY: 444.5\nZ: 92.0\n", "height": "184.0"}, {"id": "22", "name": "ChaZuo", "location": "X: 543.0\nY: 1079.0\nZ: 64.0\n", "height": "128.0"}, {"id": "23", "name": "Sugar", "location": "X: 357.0\nY: 742.0\nZ: 90.5\n", "height": "181.0"}, {"id": "24", "name": "KaoXiang", "location": "X: 1.2000000424450263e-05\nY: -6.000000212225132e-06\nZ: 144.0\n", "height": "288.0"}, {"id": "25", "name": "XiangGui", "location": "X: 194.0\nY: 655.0\nZ: 90.0\n", "height": "180.0"}, {"id": "26", "name": "BaTai", "location": "X: -20.0\nY: -6.000000212225132e-06\nZ: 144.0\n", "height": "288.0"}, {"id": "27", "name": "Chair", "location": "X: 53.99998092651367\nY: 1217.0\nZ: 34.0\n", "height": "68.0"}, {"id": "28", "name": "CoffeeCup", "location": "X: 140.0\nY: 180.0\nZ: 83.0\n", "height": "166.0"}, {"id": "29", "name": "IceMachine", "location": "X: 410.0\nY: 810.0\nZ: 115.0\n", "height": "230.0"}, {"id": "30", "name": "Box", "location": "X: 152.0\nY: 275.0\nZ: 102.0\n", "height": "204.0"}, {"id": "31", "name": "TuoPan", "location": "X: 334.0\nY: 670.0\nZ: 91.0\n", "height": "182.0"}, {"id": "32", "name": "Apple", "location": "X: 330.0\nY: 760.0\nZ: 85.0\n", "height": "170.0"}, {"id": "33", "name": "WaterCup", "location": "X: 159.99998474121094\nY: 840.0\nZ: 92.0\n", "height": "184.0"}, {"id": "34", "name": "ChaTou", "location": "X: 540.0\nY: 1092.0\nZ: 48.0\n", "height": "96.0"}, {"id": "35", "name": "Towel", "location": "X: 270.2892150878906\nY: 985.1807250976562\nZ: 92.29227447509766\n", "height": "184.5845489501953"}, {"id": "36", "name": "Cake", "location": "X: 158.99998474121094\nY: 863.0\nZ: 139.0\n", "height": "278.0"}, {"id": "37", "name": "Kettle", "location": "X: 370.0\nY: 410.0\nZ: 105.0\n", "height": "210.0"}, {"id": "38", "name": "Knife", "location": "X: 318.0\nY: 780.0\nZ: 85.0\n", "height": "170.0"}, {"id": "39", "name": "Spoon", "location": "X: 134.5\nY: 443.0\nZ: 90.0\n", "height": "180.0"}, {"id": "40", "name": "Plate", "location": "X: 360.0\nY: 740.0\nZ: 89.0\n", "height": "178.0"}, {"id": "41", "name": "ZaoTai", "location": "X: 1.2000000424450263e-05\nY: 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"84.0"}, {"id": "186", "name": "CoffeeMachine", "location": "X: 360.0\nY: 214.0\nZ: 114.0\n", "height": "114.0"}, {"id": "187", "name": "Plate", "location": "X: 163.99998474121094\nY: 856.0\nZ: 111.0\n", "height": "111.0"}, {"id": "188", "name": "Cake", "location": "X: 156.99998474121094\nY: 852.0\nZ: 139.0\n", "height": "139.0"}, {"id": "189", "name": "Bread", "location": "X: 141.0\nY: 638.0\nZ: 107.0\n", "height": "107.0"}, {"id": "190", "name": "Bread", "location": "X: 169.0\nY: 700.0\nZ: 81.19999694824219\n", "height": "81.19999694824219"}, {"id": "191", "name": "Bread", "location": "X: 161.0\nY: 648.0\nZ: 108.0\n", "height": "108.0"}, {"id": "192", "name": "Bread", "location": "X: 157.0\nY: 710.0\nZ: 108.0\n", "height": "108.0"}, {"id": "193", "name": "Bread", "location": "X: 178.0\nY: 671.0\nZ: 54.0\n", "height": "54.0"}, {"id": "194", "name": "Bread", "location": "X: 135.0\nY: 660.0\nZ: 78.0\n", "height": "78.0"}, {"id": "195", "name": "Bread", "location": "X: 175.0\nY: 668.0\nZ: 109.0\n", "height": "109.0"}, {"id": "196", "name": "Bread", "location": "X: 155.0\nY: 660.0\nZ: 80.0\n", "height": "80.0"}, {"id": "197", "name": "Bread", "location": "X: 160.0\nY: 735.0\nZ: 52.0\n", "height": "52.0"}, {"id": "198", "name": "CoffeeBag", "location": "X: 425.0\nY: 787.0\nZ: 169.0\n", "height": "169.0"}, {"id": "199", "name": "CoffeeCup", "location": "X: 130.00001525878906\nY: 170.0\nZ: 84.0\n", "height": "84.0"}, {"id": "200", "name": "CoffeeMachine", "location": "X: 350.0\nY: 154.0\nZ: 84.0\n", "height": "84.0"}, {"id": "201", "name": "CoffeeCup", "location": "X: 187.5\nY: 352.5\nZ: 105.69999694824219\n", "height": "105.69999694824219"}, {"id": "202", "name": "TuoPan", "location": "X: 179.0\nY: 470.0\nZ: 89.0\n", "height": "89.0"}, {"id": "203", "name": "BaoJing", "location": "X: 360.8000183105469\nY: -199.0\nZ: 115.0\n", "height": "115.0"}, {"id": "204", "name": "KongTiao", "location": "X: 300.5\nY: -140.0\nZ: 114.0\n", "height": "114.0"}, {"id": "205", "name": "BaoJing", "location": "X: 362.10003662109375\nY: -197.0\nZ: 115.0\n", "height": "115.0"}, {"id": "206", "name": "KaiGuan", "location": "X: 342.0000305175781\nY: -184.28216552734375\nZ: 114.0\n", "height": "114.0"}, {"id": "207", "name": "Mug", "location": "X: 377.0\nY: 206.0\nZ: 161.0\n", "height": "161.0"}, {"id": "208", "name": "Container", "location": "X: 370.0\nY: 380.0\nZ: 84.0\n", "height": "84.0"}, {"id": "209", "name": "Glass", "location": "X: 140.0\nY: 460.0\nZ: 84.0\n", "height": "84.0"}, {"id": "210", "name": "TuoPan", "location": "X: 179.0\nY: 470.0\nZ: 87.0\n", "height": "87.0"}, {"id": "211", "name": "Sugar", "location": "X: 362.0\nY: 740.0\nZ: 91.0\n", "height": "91.0"}, {"id": "212", "name": "Mug", "location": "X: 377.0\nY: 213.0\nZ: 170.0\n", "height": "170.0"}, {"id": "213", "name": "Mug", "location": "X: 377.0\nY: 313.0\nZ: 170.0\n", "height": "170.0"}, {"id": "214", "name": "Mug", "location": "X: 377.0\nY: 420.0\nZ: 161.0\n", "height": "161.0"}, {"id": "215", "name": "Glass", "location": "X: 324.0\nY: 56.000003814697266\nZ: 89.0\n", "height": "89.0"}, {"id": "216", "name": "Container", "location": "X: 370.0\nY: 370.0\nZ: 104.0\n", "height": "104.0"}, {"id": "217", "name": "TuoPan", "location": "X: 174.00001525878906\nY: 170.0\nZ: 89.0\n", "height": "89.0"}, {"id": "218", "name": "Sugar", "location": "X: 356.0\nY: 738.0\nZ: 90.5\n", "height": "90.5"}, {"id": "219", "name": "Mug", "location": "X: 377.0\nY: 306.0\nZ: 161.0\n", "height": "161.0"}, {"id": "220", "name": "Mug", "location": "X: 377.0\nY: 604.0\nZ: 161.0\n", "height": "161.0"}, {"id": "221", "name": "Mug", "location": "X: 377.0\nY: 617.0\nZ: 161.0\n", "height": "161.0"}, {"id": "222", "name": "Glass", "location": "X: 129.0\nY: 247.0\nZ: 144.5\n", "height": "144.5"}, {"id": "223", "name": "TuoPan", "location": "X: 179.0\nY: 470.0\nZ: 85.0\n", "height": "85.0"}, {"id": "224", "name": "Bread", "location": "X: 175.0\nY: 652.0\nZ: 82.0\n", "height": "82.0"}, {"id": "225", "name": "Sugar", "location": "X: 355.0\nY: 742.0\nZ: 90.5\n", "height": "90.5"}, {"id": "226", "name": "Mug", "location": "X: 377.0\nY: 123.0\nZ: 161.0\n", "height": "161.0"}, {"id": "227", "name": "Mug", "location": "X: 377.0\nY: 406.0\nZ: 161.0\n", "height": "161.0"}, {"id": "228", "name": "TuoPan", "location": "X: 334.0\nY: 670.0\nZ: 85.0\n", "height": "85.0"}, {"id": "229", "name": "Bread", "location": "X: 181.0\nY: 637.0\nZ: 54.0\n", "height": "54.0"}, {"id": "230", "name": "Bread", "location": "X: 184.0\nY: 652.0\nZ: 82.0\n", "height": "82.0"}, {"id": "231", "name": "TuoPan", "location": "X: 334.0\nY: 740.0\nZ: 85.0\n", "height": "85.0"}, {"id": "232", "name": "Sugar", "location": "X: 359.0\nY: 741.0\nZ: 90.5\n", "height": "90.5"}, {"id": "233", "name": "Bread", "location": "X: 138.0\nY: 700.0\nZ: 78.0\n", "height": "78.0"}, {"id": "234", "name": "Bread", "location": "X: 140.0\nY: 698.0\nZ: 50.0\n", "height": "50.0"}, {"id": "235", "name": "Bread", "location": "X: 165.0\nY: 660.0\nZ: 81.0\n", "height": "81.0"}] \ No newline at end of file diff --git a/robowaiter/robot/robot.py b/robowaiter/robot/robot.py index a364d1c..bc8a0bc 100644 --- a/robowaiter/robot/robot.py +++ b/robowaiter/robot/robot.py @@ -92,8 +92,9 @@ class Robot(object): else: print('Warning: have none sub task sequence') self.scene.sub_task_seq = seq - print("当前行为树为：") - print_tree_from_root(self.bt.root) + # print("当前行为树为：") + # print_tree_from_root(self.bt.root) + print("行为树扩展完成！") # 获取所有action的pre,add,del列表 def collect_action_nodes(self): diff --git a/robowaiter/scene/scene.py b/robowaiter/scene/scene.py index b9ad1b2..676899e 100644 --- a/robowaiter/scene/scene.py +++ b/robowaiter/scene/scene.py @@ -4,6 +4,8 @@ import time import grpc import numpy as np import matplotlib.pyplot as plt +from matplotlib import patches + from robowaiter.proto import camera from robowaiter.proto import semantic_map from robowaiter.algos.navigator.navigate import Navigator @@ -13,6 +15,12 @@ from robowaiter.proto import GrabSim_pb2_grpc import copy import os from robowaiter.utils import get_root_path +from sklearn.cluster import DBSCAN +from matplotlib import pyplot as plt +plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签 +plt.rcParams['axes.unicode_minus']=False #用来正常显示负号 + + root_path = get_root_path() channel = grpc.insecure_channel( @@ -32,6 +40,11 @@ def init_world(scene_num=1, mapID=11): stub.SetWorld(GrabSim_pb2.BatchMap(count=scene_num, mapID=mapID)) time.sleep(3) # wait for the map to load +def get_camera(part, scene_id=0): + # print('------------------get_camera----------------------') + action = GrabSim_pb2.CameraList(cameras=part, scene=scene_id) + return stub.Capture(action) + def show_image(camera_data): print('------------------show_image----------------------') @@ -100,6 +113,10 @@ class Scene: self.sub_task_seq = None self.show_bubble = True + # 图像分割 + self.take_picture = False + self.map_ratio = 5 + self.db = DBSCAN(eps=self.map_ratio, min_samples=int(self.map_ratio / 2)) # init robot if robot: @@ -568,7 +585,17 @@ class Scene: def move_to_obj(self,obj_id): + scene = self.status + # 抬头 + # value = [0]*21 + # for i in range(21): + # value[i] = self.status.joints[i].angle + # value[5] = 0 + # action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.RotateJoints, values=value) + # scene = stub.Do(action) + # time.sleep(1.0) + obj_info = scene.objects[obj_id] # Robot obj_x, obj_y, obj_z = obj_info.location.X, obj_info.location.Y, obj_info.location.Z @@ -587,6 +614,16 @@ class Scene: # 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]): scene = self.status + + # 抬头 + # value = [0]*21 + # for i in range(21): + # value[i] = self.status.joints[i].angle + # value[5] = 0 + # action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.RotateJoints, values=value) + # scene = stub.Do(action) + # time.sleep(1.0) + cur_pos = [scene.location.X, scene.location.Y, scene.rotation.Yaw] print("Current Position:", cur_pos, "开始任务:", self.op_dialog[op_type]) if op_type == 11 or op_type == 12: # 开关窗帘不需要移动 @@ -634,6 +671,15 @@ class Scene: # 调整空调开关、温度 def adjust_kongtiao(self,op_type): + # 低头 + value = [0]*21 + for i in range(21): + value[i] = self.status.joints[i].angle + value[5] = 30 + action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.RotateJoints, values=value) + scene = stub.Do(action) + time.sleep(1.0) + obj_loc = self.obj_loc[:] obj_loc[2] -= 5 if op_type == 13: obj_loc[1] -= 2 @@ -664,6 +710,19 @@ class Scene: def grasp_obj(self,obj_id,hand_id=1): print('------------------adjust_joints----------------------') scene = self.status + + # 低头 + value = [0]*21 + for i in range(21): + value[i] = self.status.joints[i].angle + value[5] = 30 + action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.RotateJoints, values=value) + scene = stub.Do(action) + time.sleep(1.0) + + if self.take_picture: + self.get_obstacle_point(self.db, self.status, map_ratio=self.map_ratio) + obj_info = scene.objects[obj_id] obj_x, obj_y, obj_z = obj_info.location.X, obj_info.location.Y, obj_info.location.Z if obj_info.name=="CoffeeCup": @@ -713,6 +772,19 @@ class Scene: # 实现放置操作 def release_obj(self,release_pos): print("------------------adjust_joints----------------------") + # 低头 + value = [0]*21 + for i in range(21): + value[i] = self.status.joints[i].angle + value[5] = 30 + action = GrabSim_pb2.Action(scene=self.sceneID, action=GrabSim_pb2.Action.ActionType.RotateJoints, values=value) + scene = stub.Do(action) + time.sleep(1.0) + + if self.take_picture: + self.get_obstacle_point(self.db, self.status, map_ratio=self.map_ratio) + + if release_pos==[340.0, 900.0, 99.0]: self.ik_control_joints(2, release_pos[0]-40, release_pos[1]+35, release_pos[2]) time.sleep(2.0) @@ -766,7 +838,7 @@ class Scene: scene = stub.Do(action) print(scene.info) - def navigation_move(self, cur_objs, objs_name_set, cur_obstacle_world_points, v_list, map_ratio, db, scene_id=0, map_id=11): + def navigation_move(self, plt, cur_objs, cur_obstacle_world_points, v_list, map_ratio, db, scene_id=0, map_id=11): print('------------------navigation_move----------------------') scene = stub.Observe(GrabSim_pb2.SceneID(value=scene_id)) walk_value = [scene.location.X, scene.location.Y] @@ -779,10 +851,10 @@ class Scene: 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) - cur_objs, objs_name_set = camera.get_semantic_map(GrabSim_pb2.CameraName.Head_Segment, cur_objs, - objs_name_set) + # cur_objs, objs_name_set = camera.get_semantic_map(GrabSim_pb2.CameraName.Head_Segment, cur_objs, + # objs_name_set) - cur_obstacle_world_points = camera.get_obstacle_point(db, scene, cur_obstacle_world_points,map_ratio) + cur_obstacle_world_points, cur_objs_id= camera.get_obstacle_point(plt, db, scene, cur_obstacle_world_points,map_ratio) # if scene.info == "Unreachable": @@ -801,15 +873,15 @@ class Scene: action = GrabSim_pb2.Action(scene=scene_id, action=GrabSim_pb2.Action.ActionType.WalkTo, values=walk_v) scene = stub.Do(action) - cur_objs, objs_name_set = camera.get_semantic_map(GrabSim_pb2.CameraName.Head_Segment, cur_objs, - objs_name_set) + # cur_objs, objs_name_set = camera.get_semantic_map(GrabSim_pb2.CameraName.Head_Segment, cur_objs, + # objs_name_set) - cur_obstacle_world_points = camera.get_obstacle_point(db, scene, cur_obstacle_world_points, map_ratio) + cur_obstacle_world_points, cur_objs_id= camera.get_obstacle_point(plt, db, scene, cur_obstacle_world_points, map_ratio) # if scene.info == "Unreachable": print(scene.info) - return cur_objs, objs_name_set, cur_obstacle_world_points + return cur_obstacle_world_points, cur_objs_id 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: @@ -905,3 +977,235 @@ class Scene: return True else: return False + + + + @staticmethod + def transform_co(img_data, pixel_x_, pixel_y_, depth_, scene, id=0, label=0): + im = img_data.images[0] + + # 相机外参矩阵 + out_matrix = np.array(im.parameters.matrix).reshape((4, 4)) + + d = np.frombuffer(im.data, dtype=im.dtype).reshape((im.height, im.width, im.channels)) + depth = depth_ + + # 将像素坐标转换为归一化设备坐标 + normalized_x = (pixel_x_ - im.parameters.cx) / im.parameters.fx + normalized_y = (pixel_y_ - im.parameters.cy) / im.parameters.fy + + # 将归一化设备坐标和深度值转换为相机坐标 + camera_x = normalized_x * depth + camera_y = normalized_y * depth + camera_z = depth + + # 构建相机坐标向量 + camera_coordinates = np.array([camera_x, camera_y, camera_z, 1]) + # print("物体相对相机坐标的齐次坐标: ", camera_coordinates) + + # 将相机坐标转换为机器人底盘坐标 + robot_coordinates = np.dot(out_matrix, camera_coordinates)[:3] + # print("物体的相对底盘坐标为:", robot_coordinates) + + # 将物体相对机器人底盘坐标转为齐次坐标 + robot_homogeneous_coordinates = np.array([robot_coordinates[0], -robot_coordinates[1], robot_coordinates[2], 1]) + # print("物体的相对底盘的齐次坐标为:", robot_homogeneous_coordinates) + + # 机器人坐标 + X = scene.location.X + Y = scene.location.Y + Z = 0.0 + + # 机器人旋转信息 + Roll = 0.0 + Pitch = 0.0 + Yaw = scene.rotation.Yaw + + # 构建平移矩阵 + T = np.array([[1, 0, 0, X], + [0, 1, 0, Y], + [0, 0, 1, Z], + [0, 0, 0, 1]]) + + # 构建旋转矩阵 + Rx = np.array([[1, 0, 0, 0], + [0, np.cos(Roll), -np.sin(Roll), 0], + [0, np.sin(Roll), np.cos(Roll), 0], + [0, 0, 0, 1]]) + + Ry = np.array([[np.cos(Pitch), 0, np.sin(Pitch), 0], + [0, 1, 0, 0], + [-np.sin(Pitch), 0, np.cos(Pitch), 0], + [0, 0, 0, 1]]) + + Rz = np.array([[np.cos(np.radians(Yaw)), -np.sin(np.radians(Yaw)), 0, 0], + [np.sin(np.radians(Yaw)), np.cos(np.radians(Yaw)), 0, 0], + [0, 0, 1, 0], + [0, 0, 0, 1]]) + + R = np.dot(Rz, np.dot(Ry, Rx)) + + # 构建机器人的变换矩阵 + T_robot = np.dot(T, R) + # print(T_robot) + + # 将物体的坐标从机器人底盘坐标系转换到世界坐标系 + world_coordinates = np.dot(T_robot, robot_homogeneous_coordinates)[:3] + + # if world_coordinates[0] < 200 and world_coordinates[1] <= 1050: + # world_coordinates[0] += 400 + # world_coordinates[1] += 400 + # elif world_coordinates[0] >= 200 and world_coordinates[1] <= 1050: + # world_coordinates[0] -= 550 + # world_coordinates[1] += 400 + # elif world_coordinates[0] >= 200 and world_coordinates[1] > 1050: + # world_coordinates[0] -= 550 + # world_coordinates[1] -= 1450 + # elif world_coordinates[0] < 200 and world_coordinates[1] > 1050: + # world_coordinates[0] += 400 + # world_coordinates[1] -= 1450 + # print("物体的世界坐标：", world_coordinates) + + # 世界偏移后的坐标 + world_offest_coordinates = [world_coordinates[0] + 700, world_coordinates[1] + 1400, world_coordinates[2]] + # print("物体世界偏移的坐标: ", world_offest_coordinates) + return world_coordinates + + @staticmethod + def get_obstacle_point(db, scene, map_ratio): + # db = DBSCAN(eps=4, min_samples=2) + cur_obstacle_pixel_points = [] + object_pixels = {} + colors = [ + 'red', + 'pink', + 'purple', + 'blue', + 'cyan', + 'green', + 'yellow', + 'orange', + 'brown', + 'gold', + ] + not_key_objs_id = {255, 254, 253, 107, 81} + + img_data_segment = get_camera([GrabSim_pb2.CameraName.Head_Segment]) + img_data_depth = get_camera([GrabSim_pb2.CameraName.Head_Depth]) + img_data_color = get_camera([GrabSim_pb2.CameraName.Head_Color]) + + im_segment = img_data_segment.images[0] + im_depth = img_data_depth.images[0] + im_color = img_data_color.images[0] + + d_segment = np.frombuffer(im_segment.data, dtype=im_segment.dtype).reshape( + (im_segment.height, im_segment.width, im_segment.channels)) + d_depth = np.frombuffer(im_depth.data, dtype=im_depth.dtype).reshape( + (im_depth.height, im_depth.width, im_depth.channels)) + d_color = np.frombuffer(im_color.data, dtype=im_color.dtype).reshape( + (im_color.height, im_color.width, im_color.channels)) + + items = img_data_segment.info.split(";") + objs_id = {} + for item in items: + key, value = item.split(":") + objs_id[int(key)] = value + objs_id[251] = "walker" + # plt.imshow(d_depth, cmap="gray" if "depth" in im_depth.name.lower() else None) + # plt.show() + # plt.imshow(d_segment, cmap="gray" if "depth" in im_segment.name.lower() else None) + # plt.axis("off") + # plt.title("相机分割") + # plt.show() + + d_depth = np.transpose(d_depth, (1, 0, 2)) + d_segment = np.transpose(d_segment, (1, 0, 2)) + for i in range(0, d_segment.shape[0], map_ratio): + for j in range(0, d_segment.shape[1], map_ratio): + if d_depth[i][j][0] == 600: + continue + + # if d_segment[i][j] == 96: + # print(f"apple的像素坐标：({i},{j})") + # print(f"apple的深度：{d_depth[i][j][0]}") + # print(f"apple的世界坐标: {transform_co(img_data_depth, i, j, d_depth[i][j][0], scene)}") + # if d_segment[i][j] == 113: + # print(f"kettle的像素坐标：({i},{j})") + # print(f"kettle的深度：{d_depth[i][j][0]}") + # print(f"kettle的世界坐标: {transform_co(img_data_depth, i, j, d_depth[i][j][0], scene)}") + # if d_segment[i][j][0] in obstacle_objs_id: + # cur_obstacle_pixel_points.append([i, j]) + if d_segment[i][j][0] not in not_key_objs_id: + # 首先检查键是否存在 + if d_segment[i][j][0] in object_pixels: + # 如果键存在，那么添加元组(i, j)到对应的值中 + object_pixels[d_segment[i][j][0]].append([i, j]) + else: + # 如果键不存在，那么创建一个新的键值对，其中键是d_segment[i][j][0]，值是一个包含元组(i, j)的列表 + object_pixels[d_segment[i][j][0]] = [[i, j]] + # print(cur_obstacle_pixel_points) + # for pixel in cur_obstacle_pixel_points: + # world_point = transform_co(img_data_depth, pixel[0], pixel[1], d_depth[pixel[0]][pixel[1]][0], scene) + # cur_obstacle_world_points.append([world_point[0], world_point[1]]) + # print(f"{pixel}：{[world_point[0], world_point[1]]}") + # plt.subplot(2, 2, 2) + plt.imshow(d_color, cmap="gray" if "depth" in im_depth.name.lower() else None) + # plt.axis('off') + plt.title("目标检测") + + + for key, value in object_pixels.items(): + if key == 0: + continue + if key not in objs_id.keys(): + continue + if key in [91, 84, 96, 87, 102, 106, 120, 85, 113, 101, 83, 251]: + X = np.array(value) + db.fit(X) + labels = db.labels_ + # 将数据按照聚类标签分组，并打印每个分组的数据 + for i in range(max(labels) + 1): # 从0到最大聚类标签的值 + group_data = X[labels == i] # 获取当前标签的数据 + x_max = max(p[0] for p in group_data) + y_max = max(p[1] for p in group_data) + x_min = min(p[0] for p in group_data) + y_min = min(p[1] for p in group_data) + if x_max - x_min < 10 or y_max - y_min < 10: + continue + # 在指定的位置绘制方框 + # 创建矩形框 + rect = patches.Rectangle((x_min, y_min), (x_max - x_min), (y_max - y_min), linewidth=1, + edgecolor=colors[key % 10], + facecolor='none') + plt.text(x_min, y_min, f'{objs_id[key]}', + fontdict={'family': 'serif', 'size': 10, 'color': 'green'}, ha='center', + va='center') + plt.gca().add_patch(rect) + else: + x_max = max(p[0] for p in value) + y_max = max(p[1] for p in value) + x_min = min(p[0] for p in value) + y_min = min(p[1] for p in value) + # 在指定的位置绘制方框 + # 创建矩形框 + rect = patches.Rectangle((x_min, y_min), (x_max - x_min), (y_max - y_min), linewidth=1, + edgecolor=colors[key % 10], + facecolor='none') + + plt.text(x_min, y_min, f'{objs_id[key]}', + fontdict={'family': 'serif', 'size': 10, 'color': 'green'}, + ha='center', + va='center') + plt.gca().add_patch(rect) + # point1 = min(value, key=lambda x: (x[0], x[1])) + # point2 = max(value, key=lambda x: (x[0], x[1])) + # width = point2[1] - point1[1] + # height = point2[0] - point1[0] + # rect = patches.Rectangle((0, 255), 15, 30, linewidth=1, edgecolor='g', + # facecolor='none') + + # 将矩形框添加到图像中 + # plt.gca().add_patch(rect) + + plt.show() + # return cur_obstacle_world_points diff --git a/robowaiter/scene/tasks/AEM.py b/robowaiter/scene/tasks/AEM.py index 5dc7603..63234b1 100644 --- a/robowaiter/scene/tasks/AEM.py +++ b/robowaiter/scene/tasks/AEM.py @@ -11,6 +11,8 @@ import pickle import numpy as np from matplotlib import pyplot as plt +plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签 +plt.rcParams['axes.unicode_minus']=False #用来正常显示负号 from sklearn.cluster import DBSCAN from robowaiter.scene.scene import Scene @@ -21,21 +23,20 @@ class SceneAEM(Scene): def _reset(self): pass def _run(self): + print(len(self.status.objects)) # 创建一个从白色（1）到灰色（0）的 colormap + objs = self.status.objects cur_objs = [] cur_obstacle_world_points = [] - objs_name_set = set() visited_obstacle = set() obj_json_data = [] - db = DBSCAN(eps=4, min_samples=2) + obj_count = 0 + added_info = 0 + + map_ratio = 3 - # # 创建一个颜色映射，其中0表示黑色，1表示白色 - # cmap = plt.cm.get_cmap('gray') - # cmap.set_under('black') - # cmap.set_over('white') - - + db = DBSCAN(eps=map_ratio, min_samples=int(map_ratio / 2)) file_name = '../../proto/map_1.pkl' if os.path.exists(file_name): @@ -51,11 +52,15 @@ class SceneAEM(Scene): # navigation_test(i,map_id) map_map = np.zeros((math.ceil(950 / map_ratio), math.ceil(1850 / map_ratio))) + # self.add_walker(0, 30, 520, ) + # self.add_walker(10, 30, 420) 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 + walker_count = 0 + fig = plt.figure() + goal = self.explore(map, 120) if goal is None: break - cur_objs, objs_name_set, cur_obstacle_world_points= self.navigation_move(cur_objs, objs_name_set, cur_obstacle_world_points, [[goal[0], goal[1]]], map_ratio, db,0, 11) + cur_obstacle_world_points, cur_objs_id= self.navigation_move(plt, cur_objs, cur_obstacle_world_points, [[goal[0], goal[1]]], map_ratio, db,0, 11) for point in cur_obstacle_world_points: if point[0] < -350 or point[0] > 600 or point[1] < -400 or point[1] > 1450: @@ -66,34 +71,66 @@ class SceneAEM(Scene): # extent=(-400 / map_ratio, 1450 / map_ratio, # -350 / map_ratio, 600 / map_ratio)) - # 使用imshow函数绘制图像，其中cmap参数设置颜色映射 + for i in range(len(cur_objs_id)): + if cur_objs_id[i] == "walker": + walker_count += 1 + for obj in objs: + if obj.name == cur_objs_id[i] and obj not in cur_objs: + cur_objs.append(obj) + break + + plt.subplot(2, 1, 2) # 这里的2,1表示总共2行，1列，2表示这个位置是第2个子图 plt.imshow(map_map, cmap='binary', alpha=0.5, origin='lower', extent=(-400 / map_ratio, 1450 / map_ratio, -350 / map_ratio, 600 / map_ratio)) # plt.imshow(map_map, cmap='binary', alpha=0.5, origin='lower') # plt.axis('off') + plt.title("地图构建过程") + + plt.subplot(2, 7, 14) # 这里的2,1表示总共2行，1列，2表示这个位置是第2个子图 + + # plt.text(0, 0.7, f'检测行人数量：{walker_count}', fontsize=10) + + new_add_info = len(cur_objs) - added_info + walker_count + plt.text(0, 0.5, f'新增语义信息：{new_add_info}', fontsize=10) # 在图中添加文字，x和y坐标是在这个图片大小内的相对位置，fontsize是字体大小 + added_info += new_add_info + plt.text(0, 0.3, f'已存语义信息：{added_info}', fontsize=10) # 在图中添加文字，x和y坐标是在这个图片大小内的相对位置，fontsize是字体大小 + plt.axis("off") plt.show() + print("------------当前检测到的物品信息--------------") + print(cur_objs) time.sleep(1) - print("------------物品信息--------------") - print(cur_objs) + for i in range(len(cur_objs)): - obj_json_data.append({"id":f"{i}", "name":f"{cur_objs[i].name}", "location":f"{cur_objs[i].location}", "height":f"{cur_objs[i].location.Z * 2}"}) + if cur_objs[i].name == "Desk" or cur_objs[i].name == "Chair": + obj_json_data.append({"id":f"{i}", "name":f"{cur_objs[i].name}", "location":f"{cur_objs[i].location}", "height":f"{cur_objs[i].location.Z * 2}"}) + + else: + obj_json_data.append( + {"id": f"{i}", "name": f"{cur_objs[i].name}", "location": f"{cur_objs[i].location}", + "height": f"{cur_objs[i].location.Z}"}) with open('../../proto/objs.json', 'w') as file: json.dump(obj_json_data, file) + # for i in range(-350, 600): # for j in range(-400, 1450): # i = (math.floor((i + 350) / map_ratio)) # j = (math.floor((j + 400) / map_ratio)) # if (i, j) not in visited_obstacle: # map_map[i][j] = 1 - plt.imshow(map_map, cmap='binary', alpha=0.5, origin='lower', - extent=(-400 / map_ratio, 1450 / map_ratio, - -350 / map_ratio, 600 / map_ratio)) + # plt.imshow(map_map, cmap='binary', alpha=0.5, origin='lower', + # extent=(-400 / map_ratio, 1450 / map_ratio, + # -350 / map_ratio, 600 / map_ratio)) # plt.axis('off') - plt.show() + # plt.show() print("已绘制完成地图！！！") + print("------------检测到的所有物品信息--------------") + print(obj_json_data) + # self.add_walker(0, 30, 520, ) + # self.add_walker(10, 30, 420) + # Scene.get_obstacle_point(db, Scene.status, map_ratio) if __name__ == '__main__': diff --git a/robowaiter/scene/tasks/CafeDailyOperations/VLN_all.py b/robowaiter/scene/tasks/CafeDailyOperations/VLN_all.py new file mode 100644 index 0000000..fafa549 --- /dev/null +++ b/robowaiter/scene/tasks/CafeDailyOperations/VLN_all.py @@ -0,0 +1,150 @@ +""" +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.scene_flag = 1 + self.st1 = 3 + # self.st2 = self.st1 + 30 + # self.st3 = self.st2 + 65 + self.st2 = 3 + self.st3 = 3 + self.st4 = 3 + + self.signal_event_list = [ + + # 场景1：带小女孩找阳光下的空位 + (3, self.add_walker, (5, 230, 1200)), # 0号"Girl02_C_3" + (1, self.control_walker, (0, False, 200, 60, 520, 0)), + (9, self.customer_say, (0, "早上好呀，我想找个能晒太阳的地方。")), + (-1, self.customer_say, (0,"可以带我过去嘛？")), + (0, self.control_walker, (0, False, 50, 140, 1200, 180)), # 小女孩站在了 BrightTable1 旁边就餐啦 + + + # # 场景2：有个胖胖男人点单交流并要咖啡，帮他送去角落的桌子 + # (3, self.add_walker, (5, 230, 1200)), # 小女孩 + # # # 上述准备 + (10, self.add_walker, (26, -28, -150, 90)), + (0, self.add_walker, (10, -70, -200, -45)), + (6, self.customer_say, (1, "嘿，RoboWaiter，过来一下！")), + (8, self.control_walkers_and_say, ([[[1, False, 100, -18, -200, -90, "你们这有什么饮料嘛？"]]])), # 20 胖胖男到了 BrightTable6 + (2, self.customer_say, (1, "咖啡有哪些呢？")),# 10 + (2, self.customer_say, (1,"来杯卡布奇诺吧。")), # 15 + + # # 场景3：有位女士要杯水和冰红茶 + (30 ,self.add_walkers,([[[21, 65, 1000, -90],[32, -80, 850, 135],[1, 60, 420, 135]]])), + (0, self.control_walker, (5, True, 50, 250, 1200, 180)), #设置id=4 的2小男孩随机游走红随机游走 + (0, self.add_walkers, ([[[48, 60, 520,0], [31, 60, 600, -90], [20, 60, 680, -90],[9, 60, 760, -90],[29, -290, 400, 180]]])), + + (5, self.customer_say, (6, "哎呦，今天这么多人，还有空位吗？")),# 女士问 + (15, self.customer_say, (6, "我带着孩子呢，想要宽敞亮堂的地方。")), # 女士问 + # 好的，我明白了，那么您可以选择我们的家庭亲子座，这样可以容纳您的孩子，并且更加宽敞舒适。 + # 这里可以加一下自主导航和探索，找到一个位置 + # 好的，我明白了，那么我们推荐您到大厅的桌子，那里的空间比较宽敞，环境也比较明亮，适合带着孩子一起用餐。 + (8, self.customer_say, (6, "大厅的桌子好啊，快带我去呀！")), + (15, self.control_walker, (6, False, 50,-250, 480, 0)), # #290, 400 + (3, self.customer_say, (6, "我想来杯水，帮我孩子拿个酸奶吧。")), + # ### 9号灰色男 排队排着排着，不排了 + (0, self.control_walker, (9, False, 100, 100, 760, 180)), + (0, self.control_walker, (9, True, 100, 0, 0, 180)), + # # ### 增加场景，孩子说热要开空调 或者9号随机游走和说 + (90, self.customer_say, (6, "谢谢！不用了。")), #倒水+取放酸奶 90s + + + + # # # 场景4：三人排队点单，女士要保温杯 + (6, self.control_walkers_and_say, ([[[7, False, 100, 60, 520, 180, "我昨天保温杯好像落在你们咖啡厅了，你看到了吗？"]]])), + (5, self.customer_say, (7,"你可以帮我拿来吗，我在前门的桌子前等你。")), + (1, self.control_walker,(7, False, 80, -10, 520, 90)),# 红女士在吧台前后退一步 + (1, self.control_walker, (7, False, 80, 240, 1000, -45)), # 红女士走到Table1前 + (1, self.control_walker, (8, False, 100, 60, 600, -90)), # 大胖男排队往前走一步 + (2, self.control_walker, (9, False, 100, 60, 680, -90)), # 男灰黑色排队往前走一步 + (6, self.customer_say, (7,"就是这个杯子！找到啦，好开心！")), # 红女士在Table1前 + (5, self.customer_say, (7, "不用了。")), # 红女士在Table1前 + + + + # # 场景5：三人排队点单，一人要冰红茶，一个要点心，一个没座位了赠送保温杯 + # # 场景6：大胖男点了外卖，离开啦 + (9, self.control_walkers_and_say, ([[[8, False, 100, 60, 520, 0, "给我来份午餐套餐。"]]])), #原来写了26s + (0, self.animation_reset,()), #重置任务 + (6, self.customer_say, (8, "打包吧，快点！")), + (2, self.control_walker, (9, False, 100, 60, 620, -90)), # 男灰黑色排队往前走一步 + (100, self.customer_say, (8, "谢啦，我赶时间！")), #100这个时间很合适 + (2, self.control_walker, (8, False, 250, 20, 520, -90)), # 大胖男着急得离开啦 + (2, self.control_walker, (8, False, 250, 240, -150, -90)), + (5, self.remove_walkers, ([[0,7,8]])), + + + # 场景7：最后排队那个随机游走 9号变为6号，随机游走。 + # 机器人自主发现任务，走一圈去擦桌子/拖地，碰到灰色男问好，灰色男说“太阳大，要关窗帘和空调调低” + # 开了空调 + (2, self.control_walker, (6, False, 100, 60, 520, 0)), # 10号变7号 男灰黑色排队往前,轮到他 + (2, self.customer_say, (6, "好热呀！太阳也好大！")), + (10, self.control_walkers_and_say, ([[[6, True, 100, 60, 520, 0, "谢谢，这下凉快了"]]])), + + # 场景8 结束了，删除所有顾客。此处增加自主探索发现空间比较暗，打开大厅灯 + (3, self.clean_walkers, ()), + (1, self.add_walker, (17, 60, 1000)),# 增加警察，提醒下班啦 + (3, self.control_walkers_and_say, ([[[0, False, 150, 60, 520, 0, "下班啦！别忘了打扫卫生。"]]])), + (3, self.control_walkers_and_say, ([[[0, False, 150, 60, 520, 0, "不用了。"]]])), + + ] + + def _reset(self): + self.gen_obj() + # self.add_walkers([[47, 920]]) + 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 + self.walker_followed = False + pass + + def _step(self): + + + if self.scene_flag == 1: + # 如果机器人不在 吧台 + if self.walker_followed: + return + end = [self.status.location.X, self.status.location.Y] + if end[1]>=600 or end[1]<=450 or end[0]>=250: + # if int(self.status.location.X)!=247 or int(self.status.location.X)!=520: + self.walker_followed = True + self.control_walkers_and_say([[0,False,150,end[0],end[1],90,"谢谢！"]]) + self.scene_flag += 1 + + # 获得所有顾客的名字 + # print("=================") + # for cus in self.status.walkers: + # print(cus) + # print("=================") + pass + +if __name__ == '__main__': + import os + from robowaiter.robot.robot import Robot + + robot = Robot() + + # create task + task = SceneVLM(robot) + task.reset() + task.run() diff --git a/robowaiter/scene/tasks/CafeDailyOperations/VLN_greet_and_order.py b/robowaiter/scene/tasks/CafeDailyOperations/VLN_greet_and_order.py index 9eb0349..df238a9 100644 --- a/robowaiter/scene/tasks/CafeDailyOperations/VLN_greet_and_order.py +++ b/robowaiter/scene/tasks/CafeDailyOperations/VLN_greet_and_order.py @@ -34,33 +34,32 @@ class SceneVLM(Scene): # # 场景2：有个胖胖男人点单交流并要咖啡，帮他送去角落的桌子 - # (3, self.add_walker, (5, 230, 1200)), # 小女孩 + (3, self.add_walker, (5, 230, 1200)), # 小女孩 # # # 上述准备 - # (10, self.add_walker, (26, -28, -150, 90)), - # (0, self.add_walker, (10, -70, -200, -45)), - # (6, self.customer_say, (1, "嘿，RoboWaiter，过来一下！")), - # (8, self.control_walkers_and_say, ([[[1, False, 100, -18, -200, -90, "你们这有什么饮料嘛？"]]])), # 20 胖胖男到了 BrightTable6 - # (2, self.customer_say, (1, "咖啡有哪些呢？")),# 10 - # (2, self.customer_say, (1,"来杯卡布奇诺吧。")), # 15 - # (2, self.customer_say, (1, "来杯卡布奇诺吧。")), + (10, self.add_walker, (26, -28, -150, 90)), + (0, self.add_walker, (10, -70, -200, -45)), + (6, self.customer_say, (1, "嘿，RoboWaiter，过来一下！")), + (8, self.control_walkers_and_say, ([[[1, False, 100, -18, -200, -90, "你们这有什么饮料嘛？"]]])), # 20 胖胖男到了 BrightTable6 + (2, self.customer_say, (1, "咖啡有哪些呢？")),# 10 + (2, self.customer_say, (1,"来杯卡布奇诺吧。")), # 15 # # 场景3：有位女士要杯水和冰红茶 - # (3, self.add_walker, (5, 230, 1200)), + # (30, self.add_walker, (5, 230, 1200)), # (0, self.add_walker, (26, -30, -200, -90)), # (0, self.add_walker, (10, -80, -180, -45)), # # # # 上述准备 - # # (0, self.add_walker, (21, 65, 1000, -90)), # 男 'BrightTable2': (65, 1000, 135), - # # (0, self.add_walker, (32, -80, 850, 135)), # 女 'BrightTable3': (-80, 850, 135), - # # (0, self.add_walker, (1, 60, 420, 135)), # 生成小男孩随机游走 - # (0,self.add_walkers,([[[21, 65, 1000, -90],[32, -80, 850, 135],[1, 60, 420, 135]]])), - # (0, self.control_walker, (5, True, 50, 250, 1200, 180)), #设置id=4 的2小男孩随机游走红随机游走 - # # (0, self.add_walker, (48, 60, 520,0)),# 生成他妈妈 - # # (0, self.add_walker, (31, 60, 600, -90)), # 女红色排队 7号 - # # (0, self.add_walker, (20, 60, 680, -90)), # 大胖男色排队 8号 - # # (0, self.add_walker, (9, 60, 760, -90)), # 男灰黑排队 9号 - # # (0, self.add_walker, (29, -290, 400, 180)), # 青色女人占了位置 BrightTable5 - # (0, self.add_walkers, ([[[48, 60, 520,0], [31, 60, 600, -90], [20, 60, 680, -90],[9, 60, 760, -90],[29, -290, 400, 180]]])), + # (0, self.add_walker, (21, 65, 1000, -90)), # 男 'BrightTable2': (65, 1000, 135), + # (0, self.add_walker, (32, -80, 850, 135)), # 女 'BrightTable3': (-80, 850, 135), + # (0, self.add_walker, (1, 60, 420, 135)), # 生成小男孩随机游走 + (0,self.add_walkers,([[[21, 65, 1000, -90],[32, -80, 850, 135],[1, 60, 420, 135]]])), + (0, self.control_walker, (5, True, 50, 250, 1200, 180)), #设置id=4 的2小男孩随机游走红随机游走 + (0, self.add_walker, (48, 60, 520,0)),# 生成他妈妈 + # (0, self.add_walker, (31, 60, 600, -90)), # 女红色排队 7号 + # (0, self.add_walker, (20, 60, 680, -90)), # 大胖男色排队 8号 + # (0, self.add_walker, (9, 60, 760, -90)), # 男灰黑排队 9号 + # (0, self.add_walker, (29, -290, 400, 180)), # 青色女人占了位置 BrightTable5 + (0, self.add_walkers, ([[[48, 60, 520,0], [31, 60, 600, -90], [20, 60, 680, -90],[9, 60, 760, -90],[29, -290, 400, 180]]])), # # # (5, self.customer_say, (6, "哎呦，今天这么多人，还有空位吗？")),# 女士问 # # (15, self.customer_say, (6, "我带着孩子呢，想要宽敞亮堂的地方。")), # 女士问 @@ -100,47 +99,48 @@ class SceneVLM(Scene): # (1, self.control_walker, (8, False, 100, 60, 600, -90)), # 大胖男排队往前走一步 # (2, self.control_walker, (9, False, 100, 60, 680, -90)), # 男灰黑色排队往前走一步 # (6, self.customer_say, (7,"就是这个杯子！找到啦，好开心！")), # 红女士在Table1前 - # (5, self.customer_say, (7, "不用了")), # 红女士在Table1前 + # (5, self.customer_say, (7, "不用了。")), # 红女士在Table1前 - # # 场景5：三人排队点单，一人要冰红茶，一个要点心，一个没座位了赠送保温杯 - (3, self.add_walker, (5, 230, 1200)), - (0, self.add_walker, (26, -30, -200, -90)), - (0, self.add_walker, (10, -80, -180, -45)), - (0, self.add_walker, (21, 65, 1000, -90)), # 男 'BrightTable2': (65, 1000, 135), - (0, self.add_walker, (32, -80, 850, 135)), - (0, self.add_walker, (1, 60, 220, 135)), - (0, self.add_walker, (48, 60, 320, 0)), # 生成他妈妈 - (0, self.add_walker, (31, 280, 1200, -45)), # # 女红色排队 7号找保温杯的顾客 - (0, self.add_walker, (20, 60, 680, -90)), # 大胖男排队 - (0, self.add_walker, (9, 60, 760, -90)), # 男灰黑色排队 - (0, self.add_walker, (29, -290, 400, 180)), # # 青色女人占了位置 BrightTable5 - # # 上述准备 - # # 场景6：大胖男点了外卖，离开啦 - # (9, self.control_walkers_and_say, ([[[8, False, 100, 60, 520, 0, "给我来份午餐套餐。"]]])), #原来写了26s - (0, self.animation_reset,()), #重置任务 - # (6, self.customer_say, (8, "打包吧，快点！")), - # (2, self.control_walker, (9, False, 100, 60, 620, -90)), # 男灰黑色排队往前走一步 - # # (100, self.customer_say, (8, "谢啦，我赶时间！")), #100这个时间很合适 - # (2, self.control_walker, (8, False, 250, 20, 520, -90)), # 大胖男着急得离开啦 - # (2, self.control_walker, (8, False, 250, 240, -150, -90)), - (5, self.remove_walkers, ([[0,7,8]])), - # (2, self.control_walker, (6, False, 100, 60, 520, 0)), # 9号变7号 男灰黑色排队往前,轮到他 - - - # 场景7：最后排队那个随机游走 9号变为6号，随机游走。 - # 机器人自主发现任务，走一圈去擦桌子/拖地，碰到灰色男问好，灰色男说“太阳大，要关窗帘和空调调低” - # 开了空调 - (2, self.control_walker, (6, False, 100, 60, 520, 0)), # 10号变7号 男灰黑色排队往前,轮到他 - # (2, self.customer_say, (6, "好热呀！太阳也好大！")), - # (10, self.control_walkers_and_say, ([[[6, True, 100, 60, 520, 0, "谢谢，这下凉快了"]]])), - - - # 场景8 结束了，删除所有顾客。此处增加自主探索发现空间比较暗，打开大厅灯 - (3, self.clean_walkers, ()), - (1, self.add_walker, (17, 60, 1000)),# 增加警察，提醒下班啦 - (3, self.control_walkers_and_say, ([[[0, False, 150, 60, 520, 0, "下班啦！别忘了打扫卫生。"]]])), + # # # 场景5：三人排队点单，一人要冰红茶，一个要点心，一个没座位了赠送保温杯 + # (3, self.add_walker, (5, 230, 1200)), + # (0, self.add_walker, (26, -30, -200, -90)), + # (0, self.add_walker, (10, -80, -180, -45)), + # (0, self.add_walker, (21, 65, 1000, -90)), # 男 'BrightTable2': (65, 1000, 135), + # (0, self.add_walker, (32, -80, 850, 135)), + # (0, self.add_walker, (1, 60, 220, 135)), + # (0, self.add_walker, (48, 60, 320, 0)), # 生成他妈妈 + # (0, self.add_walker, (31, 280, 1200, -45)), # # 女红色排队 7号找保温杯的顾客 + # (0, self.add_walker, (20, 60, 680, -90)), # 大胖男排队 + # (0, self.add_walker, (9, 60, 760, -90)), # 男灰黑色排队 + # (0, self.add_walker, (29, -290, 400, 180)), # # 青色女人占了位置 BrightTable5 + # # # 上述准备 + # # # 场景6：大胖男点了外卖，离开啦 + # # (9, self.control_walkers_and_say, ([[[8, False, 100, 60, 520, 0, "给我来份午餐套餐。"]]])), #原来写了26s + # (0, self.animation_reset,()), #重置任务 + # # (6, self.customer_say, (8, "打包吧，快点！")), + # # (2, self.control_walker, (9, False, 100, 60, 620, -90)), # 男灰黑色排队往前走一步 + # # # (100, self.customer_say, (8, "谢啦，我赶时间！")), #100这个时间很合适 + # # (2, self.control_walker, (8, False, 250, 20, 520, -90)), # 大胖男着急得离开啦 + # # (2, self.control_walker, (8, False, 250, 240, -150, -90)), + # (5, self.remove_walkers, ([[0,7,8]])), + # # (2, self.control_walker, (6, False, 100, 60, 520, 0)), # 9号变7号 男灰黑色排队往前,轮到他 + # + # + # # 场景7：最后排队那个随机游走 9号变为6号，随机游走。 + # # 机器人自主发现任务，走一圈去擦桌子/拖地，碰到灰色男问好，灰色男说“太阳大，要关窗帘和空调调低” + # # 开了空调 + # (2, self.control_walker, (6, False, 100, 60, 520, 0)), # 10号变7号 男灰黑色排队往前,轮到他 + # # (2, self.customer_say, (6, "好热呀！太阳也好大！")), + # # (10, self.control_walkers_and_say, ([[[6, True, 100, 60, 520, 0, "谢谢，这下凉快了"]]])), + # + # + # # 场景8 结束了，删除所有顾客。此处增加自主探索发现空间比较暗，打开大厅灯 + # (3, self.clean_walkers, ()), + # (1, self.add_walker, (17, 60, 1000)),# 增加警察，提醒下班啦 + # (3, self.control_walkers_and_say, ([[[0, False, 150, 60, 520, 0, "下班啦！别忘了打扫卫生。"]]])), + # (3, self.control_walkers_and_say, ([[[0, False, 150, 60, 520, 0, "不用了。"]]])), diff --git a/robowaiter/scene/tasks/VLM/VLM_1_order.py b/robowaiter/scene/tasks/VLM/VLM_1_order.py new file mode 100644 index 0000000..49b9d0e --- /dev/null +++ b/robowaiter/scene/tasks/VLM/VLM_1_order.py @@ -0,0 +1,45 @@ +""" +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.signal_event_list = [ + (3, self.add_walker, (20,0,700)), + (1, self.control_walker, (6, False,100, 60, 520,0)), + (1, self.customer_say, (6, "给我来杯酸奶和冰红茶，我坐在对面的桌子那儿。")), + (5, self.control_walker, (6, False, 100, -250, 480, 0)), + ] + + def _reset(self): + self.gen_obj() + + self.add_walkers([[4,1, 880], [31,250, 1200],[6,-55, 750],[10,70, -200],[27,-290, 400, 180],[26, 60,-320,90]]) + self.control_walkers(walker_loc=[[-55, 750], [70, -200], [250, 1200], [0, 880]],is_autowalk = True) + + pass + + def _run(self, op_type=10): + + 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() diff --git a/robowaiter/scene/tasks/VLM/VLM_2_AC.py b/robowaiter/scene/tasks/VLM/VLM_2_AC.py new file mode 100644 index 0000000..219a528 --- /dev/null +++ b/robowaiter/scene/tasks/VLM/VLM_2_AC.py @@ -0,0 +1,43 @@ +""" +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.signal_event_list = [ + (3, self.add_walker, (0,0,700)), + (1, self.control_walker, (6, False,100, 60, 520,0)), #[walkerID,autowalk,speed,X,Y,Yaw] + (1, self.customer_say, (6, "好热呀，想开空调，想要温度调低点！")), + (5, self.control_walker, (6, False, 200, 60, 80, 0)), + (-1, self.customer_say, (6, "谢谢！这下凉快了！")), #(-100,600) + ] + + def _reset(self): + self.gen_obj() + self.add_walkers([[4,1, 880], [31,250, 1200],[6,-55, 750],[10,70, -200],[27,-290, 400, 180],[26, 60,-320,90]]) + self.control_walkers(walker_loc=[[-55, 750], [70, -200]],is_autowalk = True) + pass + + def _run(self, op_type=10): + 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() diff --git a/robowaiter/scene/tasks/VLM/VLM_AC.py b/robowaiter/scene/tasks/VLM/VLM_AC.py new file mode 100644 index 0000000..94d2bfe --- /dev/null +++ b/robowaiter/scene/tasks/VLM/VLM_AC.py @@ -0,0 +1,142 @@ +""" +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.signal_event_list = [ + (3, self.add_walker, (0,0,700)), + (1, self.control_walker, (6, False,100, 60, 520,0)), #[walkerID,autowalk,speed,X,Y,Yaw] + (3, self.customer_say, (6, "好热呀，想开空调，想要温度调低点！")), + (5, self.control_walker, (6, False, 200, 60, 80, 0)), + (-1, self.customer_say, (6, "谢谢！这下凉快了！")), #(-100,600) + + # 有人提出要开空调和关窗帘 + # bar (60, 520) + # (28, self.add_walker, (0, 0, 0)), + # (33, self.control_walker, (7, False, 100, 60, 520, 180)), + # (35, self.customer_say, (7,"好热呀！太阳也好大！")), + # (45, self.control_walkers_and_say, ([[[7, False, 100, 270, -240, -65, "谢谢，这下凉快了！"]]])), + + # (3, self.add_walker, (0, 0, 0)), + # (1, self.control_walker, (5, False, 100, 60, 520, 180)), + # (1, self.customer_say, (5,"好热呀！太阳也好大！")), + # (-1, self.control_walkers_and_say, ([[[5, False, 100, 270, -240, -65, "谢谢，这下凉快了！"]]])), + ] + + def _reset(self): + self.gen_obj() + # self.state["condition_set"] = {'At(Robot,Bar)', 'Is(AC,Off)', + # 'Holding(Nothing)','Exist(Yogurt)','Exist(Softdrink)','On(Yogurt,Bar)','On(Softdrink,Table1)', + # 'Is(HallLight,Off)', 'Is(TubeLight,On)', 'Is(Curtain,On)', + # 'Is(Table1,Dirty)', 'Is(Floor,Dirty)', 'Is(Chairs,Dirty)'} + # # 随机生成4个自由行走，一个在 BrightTable4,BrightTable5(-20,220) + self.add_walkers([[4,1, 880], [31,250, 1200],[6,-55, 750],[10,70, -200],[27,-290, 400, 180],[26, 60,-320,90]]) + # [3,1, 880] 1号桌旁边小女孩 + # [31,250, 1200] 最角落QuietTable1女红色 + # [6,-55, 750] 1号桌附近小男孩 + # [10,70, -200] 另一边角落 QuietTable2 男黄色 + # [27,-290, 400, 180] 中间 BrightTable4 女灰 + # [26, 60,-320,90] 另一边角落 BrightTable5 红胖男 + self.control_walkers(walker_loc=[[-55, 750], [70, -200], [250, 1200], [0, 880]],is_autowalk = True) + + # 0-3男孩 4-7女孩 8-26男 + # 3男孩 31女红 32女灰 10黄色衣服男瘦 9男灰瘦 26红胖男 + # 17 是员工 police + # [0, -150,180] + + + # self.control_walkers(walker_loc=[[-55, 750]],is_autowalk = False) + # 在场景中随机增加一堆行人。 + # walker_loc = [[-55, 750], [70, -200], [250, 1200], [0, 880]] + # controls = [] + # for i in range(len(s.walkers)): + # loc = walker_loc[i] + # is_autowalk = False + # pose = GrabSim_pb2.Pose(X=loc[0], Y=loc[1], Yaw=180) + # controls.append(GrabSim_pb2.WalkerControls.WControl(id=i, autowalk=is_autowalk, speed=200, pose=pose)) + # scene = sim_client.ControlWalkers(GrabSim_pb2.WalkerControls(controls=controls, scene=scene_id)) + + # 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): + # 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() diff --git a/robowaiter/scene/tasks/VLM/VLM_order.py b/robowaiter/scene/tasks/VLM/VLM_order.py index c743023..2444308 100644 --- a/robowaiter/scene/tasks/VLM/VLM_order.py +++ b/robowaiter/scene/tasks/VLM/VLM_order.py @@ -12,10 +12,11 @@ class SceneVLM(Scene): # 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.signal_event_list = [ (3, self.add_walker, (20,0,700)), - (1, self.control_walker, (4, False,100, 60, 520,0)), #[walkerID,autowalk,speed,X,Y,Yaw] + (1, self.control_walker, (6, False,100, 60, 520,0)), #[walkerID,autowalk,speed,X,Y,Yaw] # (10, self.customer_say, (6,"给我来杯酸奶和咖啡，哦对，再倒一杯水。")), - (-1, self.customer_say, (4, "来杯酸奶吧。")), - (-1, self.control_walker, (4, False, 100, -250, 480, 0)), #(-100,600) + # (-1, self.customer_say, (6, "来杯酸奶吧。")), + (3, self.customer_say, (6, "给我来杯酸奶和冰红茶，我坐在对面的桌子那儿。")), + (5, self.control_walker, (6, False, 100, -250, 480, 0)), #(-100,600) # 有人提出要开空调和关窗帘 # bar (60, 520) @@ -24,19 +25,19 @@ class SceneVLM(Scene): # (35, self.customer_say, (7,"好热呀！太阳也好大！")), # (45, self.control_walkers_and_say, ([[[7, False, 100, 270, -240, -65, "谢谢，这下凉快了！"]]])), - (3, self.add_walker, (0, 0, 0)), - (1, self.control_walker, (5, False, 100, 60, 520, 180)), - (1, self.customer_say, (5,"好热呀！太阳也好大！")), - (-1, self.control_walkers_and_say, ([[[5, False, 100, 270, -240, -65, "谢谢，这下凉快了！"]]])), + # (3, self.add_walker, (0, 0, 0)), + # (1, self.control_walker, (5, False, 100, 60, 520, 180)), + # (1, self.customer_say, (5,"好热呀！太阳也好大！")), + # (-1, self.control_walkers_and_say, ([[[5, False, 100, 270, -240, -65, "谢谢，这下凉快了！"]]])), ] def _reset(self): self.gen_obj() - self.state["condition_set"] = {'At(Robot,Bar)', 'Is(AC,Off)', - 'Holding(Nothing)','Exist(Yogurt)','Exist(Softdrink)','On(Yogurt,Bar)','On(Softdrink,Table1)', - 'Is(HallLight,Off)', 'Is(TubeLight,On)', 'Is(Curtain,On)', - 'Is(Table1,Dirty)', 'Is(Floor,Dirty)', 'Is(Chairs,Dirty)'} - # 随机生成4个自由行走，一个在 BrightTable4,BrightTable5(-20,220) + # self.state["condition_set"] = {'At(Robot,Bar)', 'Is(AC,Off)', + # 'Holding(Nothing)','Exist(Yogurt)','Exist(Softdrink)','On(Yogurt,Bar)','On(Softdrink,Table1)', + # 'Is(HallLight,Off)', 'Is(TubeLight,On)', 'Is(Curtain,On)', + # 'Is(Table1,Dirty)', 'Is(Floor,Dirty)', 'Is(Chairs,Dirty)'} + # # 随机生成4个自由行走，一个在 BrightTable4,BrightTable5(-20,220) self.add_walkers([[4,1, 880], [31,250, 1200],[6,-55, 750],[10,70, -200],[27,-290, 400, 180],[26, 60,-320,90]]) # [3,1, 880] 1号桌旁边小女孩 # [31,250, 1200] 最角落QuietTable1女红色 diff --git a/robowaiter/utils/bt/load.py b/robowaiter/utils/bt/load.py index bf90ea9..b291971 100644 --- a/robowaiter/utils/bt/load.py +++ b/robowaiter/utils/bt/load.py @@ -13,6 +13,7 @@ def load_bt_from_ptml(scene, ptml_path, behavior_lib_path): print(f'BT loaded:') print_tree_from_root(bt.root) + # print("行为树子树加载完毕") # print(ptree.display.unicode_tree(root=bt.root, show_status=True)) return bt