from copy import deepcopy import numpy as np from core.skills.base_skill import BaseSkill, register_skill from omegaconf import DictConfig, OmegaConf from omni.isaac.core.controllers import BaseController from omni.isaac.core.robots.robot import Robot from omni.isaac.core.tasks import BaseTask from omni.isaac.core.utils.prims import get_prim_at_path from omni.isaac.core.utils.transformations import get_relative_transform from scipy.spatial.transform import Rotation as R from solver.planner import KPAMPlanner # pylint: disable=consider-using-generator,too-many-public-methods,unused-argument @register_skill class Rotate(BaseSkill): def __init__(self, robot: Robot, controller: BaseController, task: BaseTask, cfg: DictConfig, *args, **kwargs): super().__init__() self.robot = robot self.controller = controller self.task = task self.stage = task.stage self.name = cfg["name"] art_obj_name = cfg["objects"][0] self.art_obj = task.objects[art_obj_name] self.cfg = cfg # debug start: KPAMPlanner self.planner_setting = OmegaConf.to_container(cfg["planner_setting"]) self.contact_pose_index = self.planner_setting.get("contact_pose_index") self.success_threshold = self.planner_setting.get("success_threshold", 0.785) # 45 degrees if kwargs: self.world = kwargs["world"] self.draw = kwargs["draw"] # debug end: KPAMPlanner # !!! keyposes should be generated after previous skill is done self.manip_list = [] if self.cfg.get("obj_info_path", None): self.art_obj.update_articulated_info(self.cfg["obj_info_path"]) # debug start: KPAMPlanner def setup_kpam(self): self.planner = KPAMPlanner( env=self.world, robot=self.robot, object=self.art_obj, cfg_path=self.planner_setting, controller=self.controller, draw_points=self.draw, stage=self.stage, ) if "additional_labels" in self.planner_setting: new_value = self.planner_setting["additional_labels"].get( self.art_obj.asset_relative_path, self.planner.modify_actuation_motion ) self.planner.modify_actuation_motion = new_value def simple_generate_manip_cmds(self): if self.cfg.get("obj_info_path", None): self.art_obj.update_articulated_info(self.cfg["obj_info_path"]) self.setup_kpam() traj_keyframes, sample_times = self.planner.get_keypose() if len(traj_keyframes) == 0 and len(sample_times) == 0: print("No keyframes found, return empty manip_list") self.manip_list = [] return T_world_base = get_relative_transform( get_prim_at_path(self.robot.base_path), get_prim_at_path(self.task.root_prim_path) ) self.traj_keyframes = traj_keyframes self.sample_times = sample_times if self.draw: for keypose in traj_keyframes: self.draw.draw_points([(T_world_base @ np.append(keypose[:3, 3], 1))[:3]], [(0, 0, 0, 1)], [7]) # black manip_list = [] # Update p_base_ee_cur, q_base_ee_cur = self.controller.get_ee_pose() ignore_substring = deepcopy(self.controller.ignore_substring) cmd = ( p_base_ee_cur, q_base_ee_cur, "update_specific", {"ignore_substring": ignore_substring, "reference_prim_path": self.controller.reference_prim_path}, ) manip_list.append(cmd) # Update for i in range(len(self.traj_keyframes)): p_base_ee_tgt = self.traj_keyframes[i][:3, 3] q_base_ee_tgt = R.from_matrix(self.traj_keyframes[i][:3, :3]).as_quat(scalar_first=True) if i <= self.contact_pose_index - 1: cmd = (p_base_ee_tgt, q_base_ee_tgt, "open_gripper", {}) manip_list.append(cmd) if i == self.contact_pose_index - 1: # Update ignore_substring = deepcopy(self.controller.ignore_substring) parent_name = self.art_obj.prim_path.split("/")[-2] ignore_substring.append(parent_name) cmd = ( p_base_ee_tgt, q_base_ee_tgt, "update_specific", { "ignore_substring": ignore_substring, "reference_prim_path": self.controller.reference_prim_path, }, ) manip_list.append(cmd) # Update elif i == self.contact_pose_index: if "hearth" in self.art_obj.name: cmd = (p_base_ee_tgt, q_base_ee_tgt, "open_gripper", {}) manip_list.append(cmd) else: cmd = (p_base_ee_tgt, q_base_ee_tgt, "close_gripper", {}) for k in range(40): manip_list.append(cmd) else: cmd = (p_base_ee_tgt, q_base_ee_tgt, "close_gripper", {}) manip_list.append(cmd) if "hearth" in self.art_obj.name: cmd = (p_base_ee_tgt, q_base_ee_tgt, "close_gripper", {}) for k in range(40): manip_list.append(cmd) # Rotate for k in range(100): cmd = ( p_base_ee_tgt, q_base_ee_tgt, "in_plane_rotation", {"target_rotate": self.success_threshold * k / 50}, ) manip_list.append(cmd) # Rotate self.manip_list = manip_list def update(self): curr_joint_p = self.art_obj._articulation_view.get_joint_positions()[:, self.art_obj.object_joint_index] self.art_obj._articulation_view.set_joint_position_targets( positions=curr_joint_p, joint_indices=self.art_obj.object_joint_index ) def is_feasible(self, th=5): return self.controller.num_plan_failed <= th def is_subtask_done(self, t_eps=1e-3, o_eps=5e-3): assert len(self.manip_list) != 0 p_base_ee_cur, q_base_ee_cur = self.controller.get_ee_pose() p_base_ee, q_base_ee, *_ = self.manip_list[0] diff_trans = np.linalg.norm(p_base_ee_cur - p_base_ee) diff_ori = 2 * np.arccos(min(abs(np.dot(q_base_ee_cur, q_base_ee)), 1.0)) pose_flag = np.logical_and( diff_trans < t_eps, diff_ori < o_eps, ) self.plan_flag = self.controller.num_last_cmd > 10 return np.logical_or(pose_flag, self.plan_flag) def is_done(self): if len(self.manip_list) == 0: return True if self.is_subtask_done(): self.manip_list.pop(0) print("POP one manip cmd") if self.is_success(): self.manip_list.clear() print("Rotate Done") return len(self.manip_list) == 0 def is_success(self): curr_joint_p = self.art_obj._articulation_view.get_joint_positions()[:, self.art_obj.object_joint_index] distance = np.abs(curr_joint_p - self.art_obj.articulation_initial_joint_position) return distance >= np.abs(self.success_threshold)