rofunc.simulator.curi_sim
#
1. Module Contents#
1.1. Classes#
1.2. Functions#
1.3. API#
- class rofunc.simulator.curi_sim.CURISim(args)[source]#
Bases:
rofunc.simulator.base_sim.RobotSim
Initialization
Initialize the robot-centered simulator
- Parameters:
args – arguments
- show(visual_obs_flag=False)[source]#
Visualize the CURI robot :param visual_obs_flag: if True, show visual observation :param camera_props: If visual_obs_flag is True, use this camera_props to config the camera :param attached_body: If visual_obs_flag is True, use this to refer the body the camera attached to :param local_transform: If visual_obs_flag is True, use this local transform to adjust the camera pose
- run_traj_multi_rigid_bodies_with_interference(traj: List, intf_index: List, intf_mode: str, intf_forces=None, intf_torques=None, intf_joints: List = None, intf_efforts: isaacgym.torch_utils.np.ndarray = None, attracted_rigid_bodies: List = None, update_freq=0.001, save_name=None)[source]#
Run the trajectory with multiple rigid bodies with interference, the default is to run the trajectory with the left and right hand of the CURI robot. Args:
traj: a list of trajectories, each trajectory is a numpy array of shape (N, 7) intf_index: a list of the timing indices of the interference occurs intf_mode: the mode of the interference, [“actor_dof_efforts”, “body_forces”, “body_force_at_pos”] intf_forces: a tensor of shape (num_envs, num_bodies, 3), the interference forces applied to the bodies intf_torques: a tensor of shape (num_envs, num_bodies, 3), the interference torques applied to the bodies intf_joints: [list], e.g. [“panda_left_hand”] intf_efforts: array containing the efforts for all degrees of freedom of the actor. attracted_rigid_bodies: [list], e.g. [“panda_left_hand”, “panda_right_hand”] update_freq: the frequency of updating the robot pose