import tensorflow as tf from data.utils import clean_task_instruction, euler_to_rotation_matrix, rotation_matrix_to_ortho6d, \ quaternion_to_rotation_matrix def process_step(step: dict) -> dict: """ Unify the action format and clean the task instruction. DO NOT use python list, use tf.TensorArray instead. """ # Convert raw action to our action action = step['action'] # Robot action eef_pos = action[:3] eef_ang = action[3:6] eef_ang = euler_to_rotation_matrix(eef_ang) eef_ang = rotation_matrix_to_ortho6d(eef_ang) gripper_open = action[6:7] # Concatenate the action step['action'] = {} action = step['action'] arm_action = tf.concat([eef_pos, eef_ang, gripper_open], axis=0) action['arm_concat'] = arm_action action['terminate'] = step['is_terminal'] # Write the action format action['format'] = tf.constant( "eef_pos_x,eef_pos_y,eef_pos_z,eef_angle_0,eef_angle_1,eef_angle_2,eef_angle_3,eef_angle_4,eef_angle_5,gripper_open") # Convert raw state to our state # Robot state state = step['observation'] eef_pos = state['eef_pose'][:3] eef_ang = state['eef_pose'][3:] eef_ang = quaternion_to_rotation_matrix(eef_ang) eef_ang = rotation_matrix_to_ortho6d(eef_ang) eef_pos_vel = state['eef_vel'][:3] eef_ang_vel = state['eef_vel'][3:] joint_pos = state['joint_pos'] joint_vel = state['joint_vel'] grip_pos = 1 - state['state_gripper_pose'] grip_pos = tf.expand_dims(grip_pos, axis=0) # Concatenate the state state['arm_concat'] = tf.concat([ joint_pos,joint_vel,grip_pos,eef_pos,eef_ang,eef_pos_vel,eef_ang_vel], axis=0) # Write the state format state['format'] = tf.constant( "arm_joint_0_pos,arm_joint_1_pos,arm_joint_2_pos,arm_joint_3_pos,arm_joint_4_pos,arm_joint_5_pos,arm_joint_6_pos,arm_joint_0_vel,arm_joint_1_vel,arm_joint_2_vel,arm_joint_3_vel,arm_joint_4_vel,arm_joint_5_vel,arm_joint_6_vel,gripper_open,eef_pos_x,eef_pos_y,eef_pos_z,eef_angle_0,eef_angle_1,eef_angle_2,eef_angle_3,eef_angle_4,eef_angle_5,eef_vel_x,eef_vel_y,eef_vel_z,eef_angular_vel_roll,eef_angular_vel_pitch,eef_angular_vel_yaw") # Clean the task instruction # Define the replacements (old, new) as a dictionary replacements = { '_': ' ', '1f': ' ', '4f': ' ', '-': ' ', '50': ' ', '55': ' ', '56': ' ', # Refine language instruction: 'object': 'brick and insert it into the slot of the matching shape' } instr = step['language_instruction'] instr = clean_task_instruction(instr, replacements) step['observation']['natural_language_instruction'] = instr return step if __name__ == "__main__": pass