import os import numpy as np from cliport.tasks.task import Task from cliport.utils import utils class AlignBoxCorner(Task): """Pick up the randomly sized box and align one of its corners to the L-shaped marker on the tabletop.""" def __init__(self): super().__init__() self.max_steps = 3 self.lang_template = "align the brown box with the green corner" self.task_completed_desc = "done with alignment" self.additional_reset() def reset(self, env): super().reset(env) # Generate randomly shaped box. box_size = self.get_random_size(0.05, 0.15, 0.05, 0.15, 0.01, 0.06) # Add corner. dimx = (box_size[0] / 2 - 0.025 + 0.0025, box_size[0] / 2 + 0.0025) dimy = (box_size[1] / 2 + 0.0025, box_size[1] / 2 - 0.025 + 0.0025) corner_template = 'corner/corner-template.urdf' replace = {'DIMX': dimx, 'DIMY': dimy} # IMPORTANT: REPLACE THE TEMPLATE URDF corner_urdf = self.fill_template(corner_template, replace) corner_size = (box_size[0], box_size[1], 0) corner_pose = self.get_random_pose(env, corner_size) env.add_object(corner_urdf, corner_pose, 'fixed') # Add possible placing poses. theta = utils.quatXYZW_to_eulerXYZ(corner_pose[1])[2] fip_rot = utils.eulerXYZ_to_quatXYZW((0, 0, theta + np.pi)) pose1 = (corner_pose[0], fip_rot) alt_x = (box_size[0] / 2) - (box_size[1] / 2) alt_y = (box_size[1] / 2) - (box_size[0] / 2) alt_pos = (alt_x, alt_y, 0) alt_rot0 = utils.eulerXYZ_to_quatXYZW((0, 0, np.pi / 2)) alt_rot1 = utils.eulerXYZ_to_quatXYZW((0, 0, 3 * np.pi / 2)) pose2 = utils.multiply(corner_pose, (alt_pos, alt_rot0)) pose3 = utils.multiply(corner_pose, (alt_pos, alt_rot1)) # Add box. box_template = 'box/box-template.urdf' # IMPORTANT: REPLACE THE TEMPLATE URDF box_urdf = self.fill_template(box_template, {'DIM': np.float32(box_size)}) box_pose = self.get_random_pose(env, box_size) box_id = env.add_object(box_urdf, box_pose) self.color_random_brown(box_id) # Goal: box is aligned with corner (1 of 4 possible poses). self.add_goal(objs=[box_id], matches=np.int32([[1, 1, 1, 1]]), targ_poses=[corner_pose, pose1, pose2, pose3], replace=False, rotations=True, metric='pose', params=None, step_max_reward=1, symmetries=[2 * np.pi]) self.lang_goals.append(self.lang_template)