RoboTwin_image/envs/block_hammer_beat.py
2025-07-02 03:13:07 +00:00

61 lines
2.7 KiB
Python

from .base_task import Base_task
from .utils import *
import sapien
class block_hammer_beat(Base_task):
def setup_demo(self,**kwags):
super()._init(**kwags)
self.create_table_and_wall()
self.load_robot()
self.setup_planner()
self.load_camera(kwags.get('camera_w', 640),kwags.get('camera_h', 480))
self.pre_move()
self.load_actors(f"./task_config/scene_info/{self.task_name[4:]}.json")
self.step_lim = 400
def create_block_data(self, half_size):
contact_discription_list = []
test_matrix = np.array([[0,0,1,0],[1,0,0,0],[0,1,0,0],[0,0,0,1]])
test_matrix[:3,:3] = t3d.euler.euler2mat(0,0,np.pi) @ test_matrix[:3,:3]
contact_points_list = [
[[0, 0, 1, 0], [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1]], # top_down(front)
[[1, 0, 0, 0], [0, 0, -1, 0], [0, 1, 0, 0], [0, 0, 0, 1]], # top_down(right)
[[-1, 0, 0, 0], [0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 1]], # top_down(left)
[[0, 0, -1, 0], [-1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1]], # top_down(back)
]
data = {
'center': [0,0,0],
'extents': half_size,
'scale': [1,1,1], # scale
'target_pose': [[[1,0,0,0],[0,1,0,0],[0,0,1,half_size[2]],[0,0,0,1]]], # traget points matrix
'contact_points_pose' : contact_points_list, # contact points matrix list
'transform_matrix': np.eye(4).tolist(), # transform matrix
"functional_matrix": [[[1,0,0,0],[0,1,0,0],[0,0,1,half_size[2]],[0,0,0,1]]], # functional points matrix
'contact_points_discription': contact_discription_list, # contact points discription
'contact_points_group': [[0, 1, 2, 3]],
'contact_points_mask': [True],
'target_point_discription': ["The center point on the bottom of the box."]
}
return data
def pre_move(self):
render_freq = self.render_freq
self.render_freq=0
self.together_open_gripper(save_freq=None)
self.render_freq = render_freq
def play_once(self):
pass
def check_success(self):
hammer = self.actor_name_dic['hammer']
hammer_data = self.actor_data_dic['hammer_data']
block = self.actor_name_dic['block']
hammer_target_pose = self.get_actor_functional_pose(hammer,hammer_data)[:3]
block_pose = block.get_pose().p
eps = np.array([0.02,0.02])
return np.all(abs(hammer_target_pose[:2] - block_pose[:2])<eps) and hammer_target_pose[2] < 0.81 and hammer_target_pose[2] > 0.78