66 lines
2.7 KiB
Python
66 lines
2.7 KiB
Python
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from .base_task import Base_task
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from .utils import *
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import math
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import sapien
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class shoe_place(Base_task):
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def setup_demo(self,is_test = False, **kwags):
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super()._init(**kwags)
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self.create_table_and_wall()
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self.load_robot()
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self.setup_planner()
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self.load_camera(kwags.get('camera_w', 640),kwags.get('camera_h', 480))
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self.pre_move()
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if is_test:
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self.id_list = [2*i+1 for i in range(5)]
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else:
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self.id_list = [2*i for i in range(5)]
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self.load_actors(f"./task_config/scene_info/{self.task_name[4:]}.json")
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self.step_lim = 400
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def pre_move(self):
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render_freq = self.render_freq
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self.render_freq=0
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self.together_open_gripper(save_freq=None)
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self.render_freq = render_freq
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def create_block_data(self, half_size):
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contact_discription_list = []
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test_matrix = np.array([[0,0,1,0],[1,0,0,0],[0,1,0,0],[0,0,0,1]])
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test_matrix[:3,:3] = t3d.euler.euler2mat(0,0,np.pi) @ test_matrix[:3,:3]
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# print(test_matrix.tolist())
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contact_points_list = []
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data = {
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'center': [0,0,0],
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'extents': half_size,
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'scale': [1,1,1], # 缩放
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'target_pose': [[[1,0,0,0],[0,1,0,0],[0,0,1,half_size[2]],[0,0,0,1]]], # 目标点矩阵
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'contact_points_pose' : contact_points_list, # 抓取点矩阵（多个）
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'transform_matrix': np.eye(4).tolist(), # 模型到标轴的旋转矩阵
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"functional_matrix": [[0., 1., 0., 0.], [0., 0., -1., 0.], [1., 0., 0., 0.], [0., 0., 0., 1.]], # 功能点矩阵
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'contact_points_discription': contact_discription_list, # 抓取点描述
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'contact_points_group': [],
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'contact_points_mask': [],
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'target_point_discription': ["The center point on the top of the box." ]
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}
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return data
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def play_once(self):
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pass
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def check_success(self):
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shoe = self.actor_name_dic['shoe']
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shoe_pose_p = np.array(shoe.get_pose().p)
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shoe_pose_q = np.array(shoe.get_pose().q)
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if shoe_pose_q[0] < 0:
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shoe_pose_q *= -1
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target_pose_p = np.array([0,-0.08])
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target_pose_q = np.array([0.5,0.5,-0.5,-0.5])
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eps = np.array([0.05,0.02,0.05,0.05,0.05,0.05])
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endpose_z = max(self.get_right_endpose_pose().p[2], self.get_left_endpose_pose().p[2])
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return np.all(abs(shoe_pose_p[:2] - target_pose_p) < eps[:2]) and np.all(abs(shoe_pose_q - target_pose_q) < eps[-4:] ) and self.is_left_gripper_open() and self.is_right_gripper_open() |