예제 #1
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def Robot(client=None, load_geometry=False):
    """Returns a UR5 robot.

    This method serves mainly as help for writing examples, so that the code can
    stay short.

    It is intentionally capitalized to act as an almost drop-in replacement for
    the constructor of :class:`compas_fab.robots.Robot`.

    Parameters
    ----------
    client: object
        Backend client.
    load_geometry: bool

    Returns
    -------
    :class:`compas_fab.robots.Robot`
        Newly created instance of a UR5 robot.

    Examples
    --------

    >>> from compas_fab.robots.ur5 import Robot
    >>> robot = Robot()
    >>> robot.name
    'ur5'
    """

    urdf_filename = compas_fab.get(
        'universal_robot/ur_description/urdf/ur5.urdf')
    srdf_filename = compas_fab.get(
        'universal_robot/ur5_moveit_config/config/ur5.srdf')

    model = RobotModel.from_urdf_file(urdf_filename)
    semantics = RobotSemantics.from_srdf_file(srdf_filename, model)

    if load_geometry:
        loader = LocalPackageMeshLoader(compas_fab.get('universal_robot'),
                                        'ur_description')
        model.load_geometry(loader)

    robot = RobotClass(model, semantics=semantics)

    if client:
        robot.client = client

    return robot
예제 #2
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    def load_ur5(self, load_geometry=False, concavity=False):
        """"Load a UR5 robot to PyBullet.

        Parameters
        ----------
        load_geometry : :obj:`bool`, optional
            Indicate whether to load the geometry of the robot or not.
        concavity : :obj:`bool`, optional
            When ``False`` (the default), the mesh will be loaded as its
            convex hull for collision checking purposes.  When ``True``,
            a non-static mesh will be decomposed into convex parts using v-HACD.

        Returns
        -------
        :class:`compas_fab.robots.Robot`
            A robot instance.
        """
        robot_model = RobotModel.ur5(load_geometry)
        robot = Robot(robot_model, client=self)
        robot.attributes['pybullet'] = {}
        if load_geometry:
            self.cache_robot(robot, concavity)
        else:
            robot.attributes['pybullet']['cached_robot'] = robot.model
            robot.attributes['pybullet']['cached_robot_filepath'] = compas.get(
                'ur_description/urdf/ur5.urdf')

        urdf_fp = robot.attributes['pybullet']['cached_robot_filepath']

        self._load_robot_to_pybullet(urdf_fp, robot)

        srdf_filename = compas_fab.get(
            'universal_robot/ur5_moveit_config/config/ur5.srdf')
        self.load_semantics(robot, srdf_filename)

        return robot
예제 #3
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import time

from compas.datastructures import Mesh

import compas_fab
from compas_fab.backends import RosClient
from compas_fab.robots import CollisionMesh
from compas_fab.robots import PlanningScene

with RosClient('localhost') as client:
    robot = client.load_robot()

    scene = PlanningScene(robot)
    mesh = Mesh.from_stl(compas_fab.get('planning_scene/floor.stl'))
    cm = CollisionMesh(mesh, 'floor')
    scene.add_collision_mesh(cm)

    # sleep a bit before terminating the client
    #time.sleep(1)

    #scene.remove_collision_mesh('floor')

예제 #4
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import compas_fab
from compas_fab.backends import PyBulletClient
from compas_fab.robots import Configuration

with PyBulletClient() as client:
    urdf_filename = compas_fab.get(
        'universal_robot/ur_description/urdf/ur5.urdf')
    robot = client.load_robot(urdf_filename)

    configuration = Configuration.from_revolute_values(
        [-2.238, -1.153, -2.174, 0.185, 0.667, 0.])

    frame_WCF = robot.forward_kinematics(configuration)

    print("Frame in the world coordinate system")
    print(frame_WCF)
예제 #5
0
import time

import compas_fab
from compas_fab.backends.pybullet import PyBulletClient
from compas_fab.robots import AttachedCollisionMesh
from compas_fab.robots import CollisionMesh

from compas.datastructures import Mesh

with PyBulletClient() as client:
    urdf_filepath = compas_fab.get(
        'universal_robot/ur_description/urdf/ur5.urdf')
    robot = client.load_robot(urdf_filepath)

    mesh = Mesh.from_stl(compas_fab.get('planning_scene/cone.stl'))
    cm = CollisionMesh(mesh, 'tip')
    acm = AttachedCollisionMesh(cm, 'ee_link')
    client.add_attached_collision_mesh(acm, {'mass': 1, 'robot': robot})

    time.sleep(1)
    client.step_simulation()
    time.sleep(1)

    client.remove_attached_collision_mesh('tip')

    time.sleep(1)
예제 #6
0
import time

from compas.datastructures import Mesh
from compas.robots import LocalPackageMeshLoader

import compas_fab
from compas_fab.backends.pybullet import PyBulletClient
from compas_fab.robots import AttachedCollisionMesh
from compas_fab.robots import CollisionMesh

with PyBulletClient() as client:
    urdf_filepath = compas_fab.get(
        'universal_robot/ur_description/urdf/ur5.urdf')
    loader = LocalPackageMeshLoader(compas_fab.get('universal_robot'),
                                    'ur_description')
    robot = client.load_robot(urdf_filepath, [loader])

    mesh = Mesh.from_stl(compas_fab.get('planning_scene/cone.stl'))
    cm = CollisionMesh(mesh, 'tip')
    acm = AttachedCollisionMesh(cm, 'ee_link')
    client.add_attached_collision_mesh(acm, {'mass': 0.5, 'robot': robot})

    time.sleep(1)
    client.step_simulation()
    time.sleep(1)

    client.remove_attached_collision_mesh('tip', {'robot': robot})

    time.sleep(1)
def main():
    parser = argparse.ArgumentParser()
    # ur_picknplace_multiple_piece
    parser.add_argument('-p',
                        '--problem',
                        default='ur_picknplace_single_piece',
                        help='The name of the problem to solve')
    parser.add_argument('-rob',
                        '--robot',
                        default='ur3',
                        help='The type of UR robot to use.')
    parser.add_argument('-m',
                        '--plan_transit',
                        action='store_false',
                        help='Plans motions between each picking and placing')
    parser.add_argument('-v',
                        '--viewer',
                        action='store_true',
                        help='Enables the viewer during planning (slow!)')
    parser.add_argument('-s',
                        '--save_result',
                        action='store_true',
                        help='save planning results as a json file')
    parser.add_argument(
        '-scale',
        '--model_scale',
        default=0.001,
        help='model scale conversion to meter, default 0.001 (from millimeter)'
    )
    parser.add_argument('-vik',
                        '--view_ikfast',
                        action='store_true',
                        help='Visualize each ikfast solutions')
    parser.add_argument('-tres',
                        '--transit_res',
                        default=0.01,
                        help='joint resolution (rad)')
    parser.add_argument('-ros',
                        '--use_ros',
                        action='store_true',
                        help='use ros backend with moveit planners')
    parser.add_argument('-cart_ts',
                        '--cartesian_time_step',
                        default=0.1,
                        help='cartesian time step in trajectory simulation')
    parser.add_argument('-trans_ts',
                        '--transit_time_step',
                        default=0.01,
                        help='transition time step in trajectory simulation')
    parser.add_argument('-per_conf_step',
                        '--per_conf_step',
                        action='store_true',
                        help='stepping each configuration in simulation')
    args = parser.parse_args()
    print('Arguments:', args)

    VIZ = args.viewer
    VIZ_IKFAST = args.view_ikfast
    TRANSITION_JT_RESOLUTION = float(args.transit_res)
    plan_transition = args.plan_transit
    use_moveit_planner = args.use_ros

    # sim settings
    CART_TIME_STEP = args.cartesian_time_step
    TRANSITION_TIME_STEP = args.transit_time_step
    PER_CONF_STEP = args.per_conf_step

    # transition motion planner settings
    RRT_RESTARTS = 5
    RRT_ITERATIONS = 40

    # choreo pkg settings
    choreo_problem_instance_dir = compas_fab.get('choreo_instances')
    unit_geos, static_obstacles = load_assembly_package(
        choreo_problem_instance_dir, args.problem, scale=args.model_scale)

    result_save_path = os.path.join(
        choreo_problem_instance_dir, 'results',
        'choreo_result.json') if args.save_result else None

    # urdf, end effector settings
    if args.robot == 'ur3':
        # urdf_filename = compas_fab.get('universal_robot/ur_description/urdf/ur3.urdf')
        urdf_filename = compas_fab.get(
            'universal_robot/ur_description/urdf/ur3_collision_viz.urdf')
        srdf_filename = compas_fab.get(
            'universal_robot/ur3_moveit_config/config/ur3.srdf')
    else:
        urdf_filename = compas_fab.get(
            'universal_robot/ur_description/urdf/ur5.urdf')
        srdf_filename = compas_fab.get(
            'universal_robot/ur5_moveit_config/config/ur5.srdf')

    urdf_pkg_name = 'ur_description'

    ee_filename = compas_fab.get(
        'universal_robot/ur_description/meshes/' +
        'pychoreo_workshop_gripper/collision/victor_gripper_jaw03.obj')
    # ee_sep_filename = compas_fab.get('universal_robot/ur_description/meshes/' +
    #                             'pychoreo_workshop_gripper/collision/victor_gripper_jaw03_rough_sep.obj')
    # ee_decomp_file_dir = compas_fab.get('universal_robot/ur_description/meshes/' +
    #                                 'pychoreo_workshop_gripper/collision/decomp')
    # ee_decomp_file_prefix = 'victor_gripper_jaw03_decomp_'
    # decomp_parts_num = 36

    client = RosClient() if use_moveit_planner else None

    # geometry file is not loaded here
    model = RobotModel.from_urdf_file(urdf_filename)
    semantics = RobotSemantics.from_srdf_file(srdf_filename, model)
    robot = RobotClass(model, semantics=semantics, client=client)

    group = robot.main_group_name
    base_link_name = robot.get_base_link_name()
    ee_link_name = robot.get_end_effector_link_name()
    ik_joint_names = robot.get_configurable_joint_names()

    # parse end effector mesh
    # ee_meshes = [Mesh.from_obj(os.path.join(ee_decomp_file_dir, ee_decomp_file_prefix + str(i) + '.obj')) for i in range(decomp_parts_num)]
    ee_meshes = [Mesh.from_obj(ee_filename)]
    # ee_meshes = [Mesh.from_obj(ee_sep_filename)]

    # define TCP transformation
    tcp_tf = Translation([0.099, 0, 0])  # in meters
    ur5_start_conf = [0, -1.65715, 1.71108, -1.62348, 0, 0]

    if use_moveit_planner:
        # TODO: attach end effector to the robot in planning scene
        # https://github.com/compas-dev/compas_fab/issues/66
        scene = PlanningScene(robot)
        scene.remove_all_collision_objects()
        client.set_joint_positions(group, ik_joint_names, ur5_start_conf)
    else:
        scene = None

    # add static collision obstacles
    co_dict = {}
    for i, static_obs_mesh in enumerate(static_obstacles):
        # offset the table a bit...
        cm = CollisionMesh(static_obs_mesh,
                           'so_' + str(i),
                           frame=Frame.from_transformation(
                               Translation([0, 0, -0.02])))
        if use_moveit_planner:
            scene.add_collision_mesh(cm)
        else:
            co_dict[cm.id] = {}
            co_dict[cm.id]['meshes'] = [cm.mesh]
            co_dict[cm.id]['mesh_poses'] = [cm.frame]

    if use_moveit_planner:
        # See: https://github.com/compas-dev/compas_fab/issues/63#issuecomment-519525879
        time.sleep(1)
        co_dict = scene.get_collision_meshes_and_poses()

    # ======================================================
    # ======================================================
    # start pybullet environment & load pybullet robot
    connect(use_gui=VIZ)
    pb_robot = create_pb_robot_from_ros_urdf(urdf_filename,
                                             urdf_pkg_name,
                                             planning_scene=scene,
                                             ee_link_name=ee_link_name)
    ee_attachs = attach_end_effector_geometry(ee_meshes, pb_robot,
                                              ee_link_name)

    # update current joint conf and attach end effector
    pb_ik_joints = joints_from_names(pb_robot, ik_joint_names)
    pb_end_effector_link = link_from_name(pb_robot, ee_link_name)
    if not use_moveit_planner:
        set_joint_positions(pb_robot, pb_ik_joints, ur5_start_conf)
    for e_at in ee_attachs:
        e_at.assign()

    # draw TCP frame in pybullet
    if has_gui():
        TCP_pb_pose = get_TCP_pose(pb_robot,
                                   ee_link_name,
                                   tcp_tf,
                                   return_pb_pose=True)
        handles = draw_pose(TCP_pb_pose, length=0.04)
        # wait_for_user()

    # deliver ros collision meshes to pybullet
    static_obstacles_from_name = convert_meshes_and_poses_to_pybullet_bodies(
        co_dict)
    # for now...
    for so_key, so_val in static_obstacles_from_name.items():
        static_obstacles_from_name[so_key] = so_val[0]

    for unit_name, unit_geo in unit_geos.items():
        geo_bodies = []
        for sub_id, mesh in enumerate(unit_geo.mesh):
            geo_bodies.append(convert_mesh_to_pybullet_body(mesh))
        unit_geo.pybullet_bodies = geo_bodies

    # check collision between obstacles and element geometries
    assert not sanity_check_collisions(unit_geos, static_obstacles_from_name)

    # from random import shuffle
    seq_assignment = list(range(len(unit_geos)))
    # shuffle(seq_assignment)
    element_seq = {seq_id: e_id for seq_id, e_id in enumerate(seq_assignment)}

    # for key, val in element_seq.items():
    #     # element_seq[key] = 'e_' + str(val)
    #     element_seq[key] = val

    if has_gui():
        for e_id in element_seq.values():
            # for e_body in brick_from_index[e_id].body: set_pose(e_body, brick_from_index[e_id].goal_pose)
            handles.extend(
                draw_pose(unit_geos[e_id].initial_pb_pose, length=0.02))
            handles.extend(draw_pose(unit_geos[e_id].goal_pb_pose,
                                     length=0.02))
            for e_body in unit_geos[e_id].pybullet_bodies:
                set_pose(e_body, unit_geos[e_id].initial_pb_pose)
        print('pybullet env loaded.')
        # wait_for_user()
        for h in handles:
            remove_debug(h)

    saved_world = WorldSaver()

    ik_fn = ikfast_ur3.get_ik if args.robot == 'ur3' else ikfast_ur5.get_ik
    tot_traj, graph_sizes = \
    direct_ladder_graph_solve_picknplace(pb_robot, ik_joint_names, base_link_name, ee_link_name, ik_fn,
        unit_geos, element_seq, static_obstacles_from_name,
        tcp_transf=pb_pose_from_Transformation(tcp_tf),
        ee_attachs=ee_attachs,
        max_attempts=100, viz=VIZ_IKFAST, st_conf=ur5_start_conf)

    picknplace_cart_plans = divide_nested_list_chunks(tot_traj, graph_sizes)

    saved_world.restore()
    print('Cartesian planning finished.')

    # reset robot and parts for better visualization
    set_joint_positions(pb_robot, pb_ik_joints, ur5_start_conf)
    for ee in ee_attachs:
        ee.assign()
    for e_id in element_seq.values():
        for e_body in unit_geos[e_id].pybullet_bodies:
            set_pose(e_body, unit_geos[e_id].initial_pb_pose)

    # if has_gui():
    #     wait_for_user()

    def flatten_unit_geos_bodies(in_dict):
        out_list = []
        for ug in in_dict.values():
            out_list.extend(ug.pybullet_bodies)
        return out_list

    if plan_transition:
        print('Transition planning started.')

        for seq_id, unit_picknplace in enumerate(picknplace_cart_plans):
            print('----\ntransition seq#{}'.format(seq_id))
            e_id = element_seq[seq_id]

            if seq_id != 0:
                tr_start_conf = picknplace_cart_plans[seq_id -
                                                      1]['place_retreat'][-1]
            else:
                tr_start_conf = ur5_start_conf

            # obstacles=static_obstacles + cur_mo_list
            place2pick_st_conf = list(tr_start_conf)
            place2pick_goal_conf = list(
                picknplace_cart_plans[seq_id]['pick_approach'][0])
            # assert not client.is_joint_state_colliding(group, ik_joint_names, place2pick_st_conf)
            # assert not client.is_joint_state_colliding(group, ik_joint_names, place2pick_goal_conf)

            if use_moveit_planner:
                # TODO: add collision objects

                st_conf = Configuration.from_revolute_values(
                    place2pick_st_conf)
                goal_conf = Configuration.from_revolute_values(
                    place2pick_goal_conf)
                goal_constraints = robot.constraints_from_configuration(
                    goal_conf, [math.radians(1)] * 6, group)
                place2pick_jt_traj = robot.plan_motion(goal_constraints,
                                                       st_conf,
                                                       group,
                                                       planner_id='RRTConnect')
                place2pick_path = [
                    jt_pt['values']
                    for jt_pt in place2pick_jt_traj.to_data()['points']
                ]

            else:
                saved_world = WorldSaver()

                set_joint_positions(pb_robot, pb_ik_joints, place2pick_st_conf)
                for ee_a in ee_attachs:
                    ee_a.assign()

                place2pick_path = plan_joint_motion(
                    pb_robot,
                    pb_ik_joints,
                    place2pick_goal_conf,
                    attachments=ee_attachs,
                    obstacles=list(static_obstacles_from_name.values()) +
                    flatten_unit_geos_bodies(unit_geos),
                    self_collisions=True,
                    resolutions=[TRANSITION_JT_RESOLUTION] * len(pb_ik_joints),
                    restarts=RRT_RESTARTS,
                    iterations=RRT_ITERATIONS,
                )
                saved_world.restore()

                if not place2pick_path:
                    saved_world = WorldSaver()

                    print('****\nseq #{} cannot find place2pick transition'.
                          format(seq_id))
                    print('Diagnosis...')

                    cfn = get_collision_fn_diagnosis(pb_robot, pb_ik_joints, \
                        obstacles=list(static_obstacles_from_name.values()) + flatten_unit_geos_bodies(unit_geos),
                        attachments=ee_attachs, self_collisions=True)

                    print('start pose:')
                    cfn(place2pick_st_conf)

                    print('end pose:')
                    cfn(place2pick_goal_conf)

                    saved_world.restore()
                    print('Diagnosis over')

            pick2place_st_conf = picknplace_cart_plans[seq_id]['pick_retreat'][
                -1]
            pick2place_goal_conf = picknplace_cart_plans[seq_id][
                'place_approach'][0]

            if use_moveit_planner:
                st_conf = Configuration.from_revolute_values(
                    picknplace_cart_plans[seq_id]['pick_retreat'][-1])
                goal_conf = Configuration.from_revolute_values(
                    picknplace_cart_plans[seq_id]['place_approach'][0])
                goal_constraints = robot.constraints_from_configuration(
                    goal_conf, [math.radians(1)] * 6, group)
                pick2place_jt_traj = robot.plan_motion(goal_constraints,
                                                       st_conf,
                                                       group,
                                                       planner_id='RRTConnect')
                pick2place_path = [
                    jt_pt['values']
                    for jt_pt in pick2place_jt_traj.to_data()['points']
                ]
            else:
                saved_world = WorldSaver()

                # create attachement without needing to keep track of grasp...
                set_joint_positions(
                    pb_robot, pb_ik_joints,
                    picknplace_cart_plans[seq_id]['pick_retreat'][0])
                # attachs = [Attachment(robot, tool_link, invert(grasp.attach), e_body) for e_body in brick.body]
                element_attachs = [create_attachment(pb_robot, pb_end_effector_link, e_body) \
                    for e_body in unit_geos[e_id].pybullet_bodies]

                set_joint_positions(pb_robot, pb_ik_joints, pick2place_st_conf)
                for ee_a in ee_attachs:
                    ee_a.assign()
                for e_a in element_attachs:
                    e_a.assign()

                pick2place_path = plan_joint_motion(
                    pb_robot,
                    pb_ik_joints,
                    pick2place_goal_conf,
                    obstacles=list(static_obstacles_from_name.values()) +
                    flatten_unit_geos_bodies(unit_geos),
                    attachments=ee_attachs + element_attachs,
                    self_collisions=True,
                    resolutions=[TRANSITION_JT_RESOLUTION] * len(pb_ik_joints),
                    restarts=RRT_RESTARTS,
                    iterations=RRT_ITERATIONS,
                )

                saved_world.restore()

                if not pick2place_path:
                    saved_world = WorldSaver()

                    print('****\nseq #{} cannot find pick2place transition'.
                          format(seq_id))
                    print('Diagnosis...')

                    cfn = get_collision_fn_diagnosis(pb_robot, pb_ik_joints,
                        obstacles=list(static_obstacles_from_name.values()) + flatten_unit_geos_bodies(unit_geos), \
                        attachments=ee_attachs + element_attachs, self_collisions=True)

                    print('start pose:')
                    cfn(pick2place_st_conf)

                    print('end pose:')
                    cfn(pick2place_goal_conf)

                    saved_world.restore()

                    print('Diagnosis over')

            picknplace_cart_plans[seq_id]['place2pick'] = place2pick_path
            picknplace_cart_plans[seq_id]['pick2place'] = pick2place_path

            for e_body in unit_geos[e_id].pybullet_bodies:
                set_pose(e_body, unit_geos[e_id].goal_pb_pose)

            if seq_id == len(picknplace_cart_plans) - 1:
                saved_world = WorldSaver()

                set_joint_positions(
                    pb_robot, pb_ik_joints,
                    picknplace_cart_plans[seq_id]['place_retreat'][-1])
                for ee_a in ee_attachs:
                    ee_a.assign()

                return2idle_path = plan_joint_motion(
                    pb_robot,
                    pb_ik_joints,
                    ur5_start_conf,
                    obstacles=list(static_obstacles_from_name.values()) +
                    flatten_unit_geos_bodies(unit_geos),
                    attachments=ee_attachs,
                    self_collisions=True,
                    resolutions=[TRANSITION_JT_RESOLUTION] * len(pb_ik_joints),
                    restarts=RRT_RESTARTS,
                    iterations=RRT_ITERATIONS,
                )

                saved_world.restore()
                picknplace_cart_plans[seq_id]['return2idle'] = return2idle_path

        print('Transition planning finished.')

    # convert to ros JointTrajectory
    traj_json_data = []
    traj_time_count = 0.0
    for i, element_process in enumerate(picknplace_cart_plans):
        e_proc_data = {}
        for sub_proc_name, sub_process in element_process.items():
            sub_process_jt_traj_list = []
            for jt_sol in sub_process:
                sub_process_jt_traj_list.append(
                    JointTrajectoryPoint(values=jt_sol,
                                         types=[0] * 6,
                                         time_from_start=Duration(
                                             traj_time_count, 0)))
                traj_time_count += 1.0  # meaningless timestamp
            e_proc_data[sub_proc_name] = JointTrajectory(
                trajectory_points=sub_process_jt_traj_list,
                start_configuration=sub_process_jt_traj_list[0]).to_data()
        traj_json_data.append(e_proc_data)

    if result_save_path:
        with open(result_save_path, 'w+') as outfile:
            json.dump(traj_json_data, outfile, indent=4)
            print('planned trajectories saved to {}'.format(result_save_path))

    print('\n*************************\nplanning completed. Simulate?')
    if has_gui():
        wait_for_user()

    for e_id in element_seq.values():
        for e_body in unit_geos[e_id].pybullet_bodies:
            set_pose(e_body, unit_geos[e_id].initial_pb_pose)

    display_picknplace_trajectories(pb_robot, ik_joint_names, ee_link_name,
                                    unit_geos, traj_json_data, \
                                    ee_attachs=ee_attachs,
                                    cartesian_time_step=CART_TIME_STEP, transition_time_step=TRANSITION_TIME_STEP, step_sim=True, per_conf_step=PER_CONF_STEP)

    if use_moveit_planner: scene.remove_all_collision_objects()
def main():
    choreo_problem_instance_dir = compas_fab.get('choreo_instances')
    result_save_path = os.path.join(choreo_problem_instance_dir, 'results',
                                    'choreo_result.json')
    with open(result_save_path, 'r') as f:
        json_data = json.loads(f.read())

    traj_time_cnt = 0.0
    max_jt_vel = 0.2
    max_jt_acc = 0.1
    last_jt_pt = None

    # pybullet traj preview settings
    pybullet_preview = True
    PB_VIZ_CART_TIME_STEP = 0.05
    PB_VIZ_TRANS_TIME_STEP = 0.04
    PB_VIZ_PER_CONF_SIM = False

    urdf_filename = compas_fab.get(
        'universal_robot/ur_description/urdf/ur5.urdf')
    srdf_filename = compas_fab.get(
        'universal_robot/ur5_moveit_config/config/ur5.srdf')
    urdf_pkg_name = 'ur_description'

    ee_filename = compas_fab.get(
        'universal_robot/ur_description/meshes/' +
        'pychoreo_workshop_gripper/collision/victor_gripper_jaw03.obj')

    # [0.0, -94.94770102010436, 98.0376624092449, -93.01855212389889, 0.0, 0.0]
    # UR=192.168.0.30, Linux=192.168.0.1, Windows=192.168.0.2
    # the following host IP should agree with the Linux machine
    host_ip = '192.168.0.1' if REAL_EXECUTION else 'localhost'
    with RosClient(host=host_ip, port=9090) as client:
        client.on_ready(
            lambda: print('Is ROS connected?', client.is_connected))

        # get current configuration
        listener = roslibpy.Topic(client, JOINT_TOPIC_NAME,
                                  'sensor_msgs/JointState')
        msg_getter = MsgGetter()
        listener.subscribe(msg_getter.receive_msg)
        time.sleep(2)
        last_seen_state = msg_getter.get_msg()
        print('current jt state: {}'.format(last_seen_state['position']))

        model = RobotModel.from_urdf_file(urdf_filename)
        semantics = RobotSemantics.from_srdf_file(srdf_filename, model)
        robot = RobotClass(model, semantics=semantics, client=client)
        group = robot.main_group_name
        joint_names = robot.get_configurable_joint_names()
        # base_link_name = robot.get_base_link_name()
        ee_link_name = robot.get_end_effector_link_name()

        if pybullet_preview:
            from conrob_pybullet import connect
            from compas_fab.backends.ros.plugins_choreo import display_trajectory_chunk
            from compas_fab.backends.pybullet import attach_end_effector_geometry, \
            convert_mesh_to_pybullet_body, create_pb_robot_from_ros_urdf

            connect(use_gui=True)
            pb_robot = create_pb_robot_from_ros_urdf(urdf_filename,
                                                     urdf_pkg_name,
                                                     ee_link_name=ee_link_name)
            ee_meshes = [Mesh.from_obj(ee_filename)]
            ee_attachs = attach_end_effector_geometry(ee_meshes, pb_robot,
                                                      ee_link_name)

        st_conf = Configuration.from_revolute_values(
            last_seen_state['position'])
        goal_conf = Configuration.from_revolute_values(
            json_data[0]['place2pick']['start_configuration']['values'])
        goal_constraints = robot.constraints_from_configuration(
            goal_conf, [math.radians(1)] * 6, group)
        init_traj_raw = robot.plan_motion(goal_constraints,
                                          st_conf,
                                          group,
                                          planner_id='RRTStar')
        init_traj = traj_reparam(init_traj_raw,
                                 max_jt_vel,
                                 max_jt_acc,
                                 inspect_sol=False)

        if pybullet_preview:
            display_trajectory_chunk(pb_robot, joint_names,
                                     init_traj.to_data(), \
                                     ee_attachs=ee_attachs, grasped_attach=[],
                                     time_step=PB_VIZ_TRANS_TIME_STEP, step_sim=True, per_conf_step=PB_VIZ_PER_CONF_SIM)

        print('************\nexecuting init transition')
        exec_jt_traj(client, joint_names, init_traj)

        print('executed?')
        input()

        for seq_id, e_process_data in enumerate(json_data):
            print('************\nexecuting #{} picknplace process'.format(
                seq_id))

            # open gripper
            gripper_srv_call(client, state=0)

            print(
                '=====\nexecuting #{} place-retreat to pick-approach transition process'
                .format(seq_id))
            traj_data = e_process_data['place2pick']
            ros_jt_traj_raw = JointTrajectory.from_data(traj_data)
            ros_jt_traj = traj_reparam(ros_jt_traj_raw,
                                       max_jt_vel,
                                       max_jt_acc,
                                       inspect_sol=False)

            if pybullet_preview:
                display_trajectory_chunk(pb_robot, joint_names,
                                        ros_jt_traj.to_data(), \
                                        ee_attachs=ee_attachs, grasped_attach=[],
                                        time_step=PB_VIZ_TRANS_TIME_STEP, step_sim=True, per_conf_step=PB_VIZ_PER_CONF_SIM)
            exec_jt_traj(client, joint_names, ros_jt_traj)

            print('=====\nexecuting #{} pick-approach to pick-grasp process'.
                  format(seq_id))
            traj_data = e_process_data['pick_approach']
            ros_jt_traj_raw = JointTrajectory.from_data(traj_data)
            ros_jt_traj = traj_reparam(ros_jt_traj_raw,
                                       max_jt_vel,
                                       max_jt_acc,
                                       inspect_sol=False)
            if pybullet_preview:
                display_trajectory_chunk(pb_robot, joint_names,
                                        ros_jt_traj.to_data(), \
                                        ee_attachs=ee_attachs, grasped_attach=[],
                                        time_step=PB_VIZ_CART_TIME_STEP, step_sim=True, per_conf_step=PB_VIZ_PER_CONF_SIM)

            exec_jt_traj(client, joint_names, ros_jt_traj)

            print('executed?')
            input()

            # close gripper
            gripper_srv_call(client, state=1)

            print('=====\nexecuting #{} pick-grasp to pick-retreat process'.
                  format(seq_id))
            traj_data = e_process_data['pick_retreat']
            ros_jt_traj_raw = JointTrajectory.from_data(traj_data)
            ros_jt_traj = traj_reparam(ros_jt_traj_raw,
                                       max_jt_vel,
                                       max_jt_acc,
                                       inspect_sol=False)
            if pybullet_preview:
                display_trajectory_chunk(pb_robot, joint_names,
                                        ros_jt_traj.to_data(), \
                                        ee_attachs=ee_attachs, grasped_attach=[],
                                        time_step=PB_VIZ_CART_TIME_STEP, step_sim=True, per_conf_step=PB_VIZ_PER_CONF_SIM)

            exec_jt_traj(client, joint_names, ros_jt_traj)

            print('executed?')
            input()

            print(
                '=====\nexecuting #{} pick-retreat to place-approach transition process'
                .format(seq_id))
            traj_data = e_process_data['pick2place']
            ros_jt_traj_raw = JointTrajectory.from_data(traj_data)
            ros_jt_traj = traj_reparam(ros_jt_traj_raw,
                                       max_jt_vel,
                                       max_jt_acc,
                                       inspect_sol=False)
            if pybullet_preview:
                display_trajectory_chunk(pb_robot, joint_names,
                                        ros_jt_traj.to_data(), \
                                        ee_attachs=ee_attachs, grasped_attach=[],
                                        time_step=PB_VIZ_TRANS_TIME_STEP, step_sim=True, per_conf_step=PB_VIZ_PER_CONF_SIM)

            exec_jt_traj(client, joint_names, ros_jt_traj)

            print('executed?')
            input()

            print('=====\nexecuting #{} place-approach to place-grasp process'.
                  format(seq_id))
            traj_data = e_process_data['place_approach']
            ros_jt_traj_raw = JointTrajectory.from_data(traj_data)
            ros_jt_traj = traj_reparam(ros_jt_traj_raw,
                                       max_jt_vel,
                                       max_jt_acc,
                                       inspect_sol=False)
            if pybullet_preview:
                display_trajectory_chunk(pb_robot, joint_names,
                                        ros_jt_traj.to_data(), \
                                        ee_attachs=ee_attachs, grasped_attach=[],
                                        time_step=PB_VIZ_CART_TIME_STEP, step_sim=True, per_conf_step=PB_VIZ_PER_CONF_SIM)

            exec_jt_traj(client, joint_names, ros_jt_traj)

            # open gripper
            gripper_srv_call(client, state=0)

            print('executed?')
            input()

            print('=====\nexecuting #{} place-grasp to place-retreat process'.
                  format(seq_id))
            traj_data = e_process_data['place_retreat']
            ros_jt_traj_raw = JointTrajectory.from_data(traj_data)
            ros_jt_traj = traj_reparam(ros_jt_traj_raw,
                                       max_jt_vel,
                                       max_jt_acc,
                                       inspect_sol=False)
            if pybullet_preview:
                display_trajectory_chunk(pb_robot, joint_names,
                                        ros_jt_traj.to_data(), \
                                        ee_attachs=ee_attachs, grasped_attach=[],
                                        time_step=PB_VIZ_CART_TIME_STEP, step_sim=True, per_conf_step=PB_VIZ_PER_CONF_SIM)
            exec_jt_traj(client, joint_names, ros_jt_traj)

            print('executed?')
            input()

        if 'return2idle' in json_data[-1]:
            print('=====\nexecuting #{} return-to-idle transition process'.
                  format(seq_id))
            traj_data = e_process_data['return2idle']
            ros_jt_traj_raw = JointTrajectory.from_data(traj_data)
            ros_jt_traj = traj_reparam(ros_jt_traj_raw,
                                       max_jt_vel,
                                       max_jt_acc,
                                       inspect_sol=False)
            if pybullet_preview:
                display_trajectory_chunk(pb_robot, joint_names,
                                        ros_jt_traj.to_data(), \
                                        ee_attachs=ee_attachs, grasped_attach=[],
                                        time_step=PB_VIZ_TRANS_TIME_STEP, step_sim=True, per_conf_step=PB_VIZ_PER_CONF_SIM)
            exec_jt_traj(client, joint_names, ros_jt_traj)
예제 #9
0
from compas.geometry import Frame
from compas.robots import LocalPackageMeshLoader
import compas_fab
from compas_fab.backends.kinematics import AnalyticalInverseKinematics
from compas_fab.backends import PyBulletClient

urdf_filename = compas_fab.get('universal_robot/ur_description/urdf/ur5.urdf')
srdf_filename = compas_fab.get(
    'universal_robot/ur5_moveit_config/config/ur5.srdf')

frame_WCF = Frame((0.381, 0.093, 0.382), (0.371, -0.292, -0.882),
                  (0.113, 0.956, -0.269))

with PyBulletClient(connection_type='direct') as client:

    # Load UR5
    loader = LocalPackageMeshLoader(compas_fab.get('universal_robot'),
                                    'ur_description')
    robot = client.load_robot(urdf_filename, [loader])
    client.load_semantics(robot, srdf_filename)

    ik = AnalyticalInverseKinematics(client)
    # set a new IK function
    client.inverse_kinematics = ik.inverse_kinematics

    options = {"solver": "ur5", "check_collision": True, "keep_order": True}

    for solution in robot.iter_inverse_kinematics(frame_WCF, options=options):
        print(solution)
예제 #10
0
import compas
from compas.geometry import Frame
from compas.robots.configuration import Configuration

import compas_fab
from compas_fab.backends import AnalyticalInverseKinematics
from compas_fab.robots.ur5 import Robot

if not compas.IPY:
    from compas_fab.backends import AnalyticalPyBulletClient

urdf_filename = compas_fab.get('universal_robot/ur_description/urdf/ur5.urdf')
srdf_filename = compas_fab.get(
    'universal_robot/ur5_moveit_config/config/ur5.srdf')


def test_inverse_kinematics():
    ik = AnalyticalInverseKinematics()
    robot = Robot()
    frame_WCF = Frame((0.381, 0.093, 0.382), (0.371, -0.292, -0.882),
                      (0.113, 0.956, -0.269))
    # set the solver later
    solutions = list(
        ik.inverse_kinematics(robot,
                              frame_WCF,
                              start_configuration=None,
                              group=None,
                              options={"solver": "ur5"}))
    assert (len(solutions) == 8)
    joint_positions, _ = solutions[0]
    correct = Configuration.from_revolute_values(
예제 #11
0
def single_place_check(seq_id,
                       assembly_json_path,
                       customized_sequence=[],
                       num_cart_steps=10,
                       robot_model='ur3',
                       enable_viewer=True,
                       view_ikfast=False,
                       tcp_tf_list=[1e-3 * 80.525, 0, 0],
                       scale=1,
                       diagnosis=False,
                       viz_time_gap=0.5):

    # # rescaling
    # # TODO: this should be done when the Assembly object is made
    unit_geos, static_obstacle_meshes = load_assembly_package(
        assembly_json_path, scale=scale)
    assert seq_id < len(unit_geos)

    if customized_sequence:
        unit_geo = unit_geos[customized_sequence[seq_id]]
    else:
        unit_geo = unit_geos[seq_id]

    # urdf, end effector settings
    if robot_model == 'ur3':
        urdf_filename = compas_fab.get(
            'universal_robot/ur_description/urdf/ur3.urdf')
        srdf_filename = compas_fab.get(
            'universal_robot/ur3_moveit_config/config/ur3.srdf')
    else:
        urdf_filename = compas_fab.get(
            'universal_robot/ur_description/urdf/ur5.urdf')
        srdf_filename = compas_fab.get(
            'universal_robot/ur5_moveit_config/config/ur5.srdf')
    urdf_pkg_name = 'ur_description'

    ee_filename = compas_fab.get(
        'universal_robot/ur_description/meshes/' +
        'dms_2019_gripper/collision/190907_Gripper_05.obj')

    # geometry file is not loaded here
    model = RobotModel.from_urdf_file(urdf_filename)
    semantics = RobotSemantics.from_srdf_file(srdf_filename, model)
    robot = RobotClass(model, semantics=semantics)

    base_link_name = robot.get_base_link_name()
    ee_link_name = robot.get_end_effector_link_name()
    ik_joint_names = robot.get_configurable_joint_names()
    disabled_link_names = semantics.get_disabled_collisions()

    # parse end effector mesh
    ee_meshes = [Mesh.from_obj(ee_filename)]
    tcp_tf = Translation(tcp_tf_list)

    # ======================================================
    # ======================================================
    # start pybullet environment & load pybullet robot
    connect(use_gui=enable_viewer)
    camera_base_pt = (0, 0, 0)
    camera_pt = np.array(camera_base_pt) + np.array([1, 0, 0.5])
    set_camera_pose(tuple(camera_pt), camera_base_pt)

    pb_robot = create_pb_robot_from_ros_urdf(urdf_filename,
                                             urdf_pkg_name,
                                             ee_link_name=ee_link_name)
    ee_attachs = attach_end_effector_geometry(ee_meshes, pb_robot,
                                              ee_link_name)

    # update current joint conf and attach end effector
    pb_ik_joints = joints_from_names(pb_robot, ik_joint_names)
    pb_end_effector_link = link_from_name(pb_robot, ee_link_name)
    robot_start_conf = [0, -1.65715, 1.71108, -1.62348, 0, 0]
    set_joint_positions(pb_robot, pb_ik_joints, robot_start_conf)
    for e_at in ee_attachs:
        e_at.assign()

    # viz handles
    handles = []

    # convert mesh into pybullet bodies
    # TODO: this conversion should be moved into UnitGeometry
    geo_bodies = []
    for mesh in unit_geo.mesh:
        geo_bodies.append(convert_mesh_to_pybullet_body(mesh))
    unit_geo.pybullet_bodies = geo_bodies

    static_obstacles = []
    for so_mesh in static_obstacle_meshes:
        static_obstacles.append(convert_mesh_to_pybullet_body(so_mesh))

    if customized_sequence:
        assembled_element_ids = [
            customized_sequence[seq_iter] for seq_iter in range(seq_id)
        ]
    else:
        assembled_element_ids = list(range(seq_id))

    print('assembled_ids: ', assembled_element_ids)

    for prev_e_id in assembled_element_ids:
        other_unit_geo = unit_geos[prev_e_id]
        print('other unit geo: ', other_unit_geo)
        for _, mesh in enumerate(other_unit_geo.mesh):
            pb_e = convert_mesh_to_pybullet_body(mesh)
            set_pose(pb_e, other_unit_geo.goal_pb_pose)
            static_obstacles.append(pb_e)

    # check collision between obstacles and element geometries
    # assert not sanity_check_collisions([unit_geo], static_obstacles_from_name)

    ik_fn = ikfast_ur3.get_ik if robot_model == 'ur3' else ikfast_ur5.get_ik

    return quick_check_place_feasibility(
        pb_robot,
        ik_joint_names,
        base_link_name,
        ee_link_name,
        ik_fn,
        unit_geo,
        num_cart_steps=num_cart_steps,
        static_obstacles=static_obstacles,
        self_collisions=True,
        mount_link_from_tcp_pose=pb_pose_from_Transformation(tcp_tf),
        ee_attachs=ee_attachs,
        viz=view_ikfast,
        disabled_collision_link_names=disabled_link_names,
        diagnosis=diagnosis,
        viz_time_gap=viz_time_gap)
예제 #12
0
def viz_saved_traj(traj_save_path,
                   assembly_json_path,
                   element_seq,
                   from_seq_id,
                   to_seq_id,
                   cart_ts=0.01,
                   trans_ts=0.01,
                   scale=0.001,
                   robot_model='ur3',
                   per_conf_step=False,
                   step_sim=False):

    assert os.path.exists(traj_save_path) and os.path.exists(
        assembly_json_path)
    # rescaling
    # TODO: this should be done when the Assembly object is made
    unit_geos, static_obstacle_meshes = load_assembly_package(
        assembly_json_path, scale=scale)

    # urdf, end effector settings
    if robot_model == 'ur3':
        urdf_filename = compas_fab.get(
            'universal_robot/ur_description/urdf/ur3.urdf')
        # urdf_filename = compas_fab.get('universal_robot/ur_description/urdf/ur3_collision_viz.urdf')
        srdf_filename = compas_fab.get(
            'universal_robot/ur3_moveit_config/config/ur3.srdf')
    else:
        urdf_filename = compas_fab.get(
            'universal_robot/ur_description/urdf/ur5.urdf')
        srdf_filename = compas_fab.get(
            'universal_robot/ur5_moveit_config/config/ur5.srdf')

    urdf_pkg_name = 'ur_description'

    ee_filename = compas_fab.get(
        'universal_robot/ur_description/meshes/' +
        'dms_2019_gripper/collision/190907_Gripper_05.obj')

    model = RobotModel.from_urdf_file(urdf_filename)
    semantics = RobotSemantics.from_srdf_file(srdf_filename, model)
    robot = RobotClass(model, semantics=semantics)
    ik_joint_names = robot.get_configurable_joint_names()
    ee_link_name = robot.get_end_effector_link_name()

    connect(use_gui=True)
    camera_base_pt = (0, 0, 0)
    camera_pt = np.array(camera_base_pt) + np.array([1, 0, 0.5])
    set_camera_pose(tuple(camera_pt), camera_base_pt)

    pb_robot = create_pb_robot_from_ros_urdf(urdf_filename,
                                             urdf_pkg_name,
                                             ee_link_name=ee_link_name)
    ee_meshes = [Mesh.from_obj(ee_filename)]
    ee_attachs = attach_end_effector_geometry(ee_meshes, pb_robot,
                                              ee_link_name)

    static_obstacles = []
    for so_mesh in static_obstacle_meshes:
        static_obstacles.append(convert_mesh_to_pybullet_body(so_mesh))

    for unit_name, unit_geo in unit_geos.items():
        geo_bodies = []
        for sub_id, mesh in enumerate(unit_geo.mesh):
            geo_bodies.append(convert_mesh_to_pybullet_body(mesh))
        unit_geo.pybullet_bodies = geo_bodies

    if os.path.exists(traj_save_path):
        with open(traj_save_path, 'r') as f:
            traj_json_data = json.loads(f.read())

        for e_id in element_seq:
            for e_body in unit_geos[e_id].pybullet_bodies:
                set_pose(e_body, unit_geos[e_id].initial_pb_pose)

        display_picknplace_trajectories(pb_robot, ik_joint_names, ee_link_name,
                                        unit_geos, traj_json_data, \
                                        element_seq=element_seq,
                                        from_seq_id=from_seq_id, to_seq_id=to_seq_id,
                                        ee_attachs=ee_attachs,
                                        cartesian_time_step=cart_ts,
                                        transition_time_step=trans_ts, step_sim=step_sim, per_conf_step=per_conf_step)
    else:
        print('no saved traj found at: ', traj_save_path)
예제 #13
0
def sequenced_picknplace_plan(
        assembly_json_path,
        robot_model='ur3',
        pick_from_same_rack=True,
        customized_sequence=[],
        from_seq_id=0,
        to_seq_id=None,
        num_cart_steps=10,
        enable_viewer=True,
        plan_transit=True,
        transit_res=0.01,
        view_ikfast=False,
        tcp_tf_list=[1e-3 * 80.525, 0, 0],
        robot_start_conf=[0, -1.65715, 1.71108, -1.62348, 0, 0],
        scale=1,
        result_save_path='',
        sim_traj=True,
        cart_ts=0.1,
        trans_ts=0.01,
        per_conf_step=False,
        step_sim=False):

    # parser.add_argument('-vik', '--view_ikfast', action='store_true', help='Visualize each ikfast solutions')
    # parser.add_argument('-per_conf_step', '--per_conf_step', action='store_true', help='stepping each configuration in simulation')

    # transition motion planner settings
    RRT_RESTARTS = 5
    RRT_ITERATIONS = 40

    # rescaling
    # TODO: this should be done when the Assembly object is made
    unit_geos, static_obstacles = load_assembly_package(assembly_json_path,
                                                        scale=scale)

    # urdf, end effector settings
    if robot_model == 'ur3':
        urdf_filename = compas_fab.get(
            'universal_robot/ur_description/urdf/ur3.urdf')
        # urdf_filename = compas_fab.get('universal_robot/ur_description/urdf/ur3_collision_viz.urdf')
        srdf_filename = compas_fab.get(
            'universal_robot/ur3_moveit_config/config/ur3.srdf')
    else:
        urdf_filename = compas_fab.get(
            'universal_robot/ur_description/urdf/ur5.urdf')
        srdf_filename = compas_fab.get(
            'universal_robot/ur5_moveit_config/config/ur5.srdf')

    urdf_pkg_name = 'ur_description'

    ee_filename = compas_fab.get(
        'universal_robot/ur_description/meshes/' +
        'dms_2019_gripper/collision/190907_Gripper_05.obj')

    # geometry file is not loaded here
    model = RobotModel.from_urdf_file(urdf_filename)
    semantics = RobotSemantics.from_srdf_file(srdf_filename, model)
    robot = RobotClass(model, semantics=semantics)

    base_link_name = robot.get_base_link_name()
    ee_link_name = robot.get_end_effector_link_name()
    ik_joint_names = robot.get_configurable_joint_names()
    disabled_link_names = semantics.get_disabled_collisions()

    # parse end effector mesh
    ee_meshes = [Mesh.from_obj(ee_filename)]
    tcp_tf = Translation(tcp_tf_list)

    # add static collision obstacles
    co_dict = {}
    for i, static_obs_mesh in enumerate(static_obstacles):
        cm = CollisionMesh(static_obs_mesh, 'so_' + str(i))
        co_dict[cm.id] = {}
        co_dict[cm.id]['meshes'] = [cm.mesh]
        co_dict[cm.id]['mesh_poses'] = [cm.frame]

    # ======================================================
    # ======================================================
    # start pybullet environment & load pybullet robot
    connect(use_gui=enable_viewer)

    camera_base_pt = (0, 0, 0)
    camera_pt = np.array(camera_base_pt) + np.array([1, 0, 0.5])
    set_camera_pose(tuple(camera_pt), camera_base_pt)

    pb_robot = create_pb_robot_from_ros_urdf(urdf_filename,
                                             urdf_pkg_name,
                                             ee_link_name=ee_link_name)
    ee_attachs = attach_end_effector_geometry(ee_meshes, pb_robot,
                                              ee_link_name)

    # update current joint conf and attach end effector
    pb_ik_joints = joints_from_names(pb_robot, ik_joint_names)
    pb_end_effector_link = link_from_name(pb_robot, ee_link_name)
    set_joint_positions(pb_robot, pb_ik_joints, robot_start_conf)
    for e_at in ee_attachs:
        e_at.assign()

    # draw TCP frame in pybullet
    handles = []
    if has_gui() and view_ikfast:
        TCP_pb_pose = get_TCP_pose(pb_robot,
                                   ee_link_name,
                                   tcp_tf,
                                   return_pb_pose=True)
        handles = draw_pose(TCP_pb_pose, length=0.04)
        # wait_for_user()

    # deliver ros collision meshes to pybullet
    so_lists_from_name = convert_meshes_and_poses_to_pybullet_bodies(co_dict)
    static_obstacles_from_name = {}
    for so_key, so_val in so_lists_from_name.items():
        for so_i, so_item in enumerate(so_val):
            static_obstacles_from_name[so_key + '_' + str(so_i)] = so_item

    for unit_name, unit_geo in unit_geos.items():
        geo_bodies = []
        for sub_id, mesh in enumerate(unit_geo.mesh):
            geo_bodies.append(convert_mesh_to_pybullet_body(mesh))
        unit_geo.pybullet_bodies = geo_bodies

    # check collision between obstacles and element geometries
    assert not sanity_check_collisions(unit_geos, static_obstacles_from_name)

    # from random import shuffle
    seq_assignment = customized_sequence or list(range(len(unit_geos)))
    element_seq = {seq_id: e_id for seq_id, e_id in enumerate(seq_assignment)}

    to_seq_id = to_seq_id or len(element_seq) - 1
    assert 0 <= from_seq_id and from_seq_id < len(element_seq)
    assert from_seq_id <= to_seq_id and to_seq_id < len(element_seq)

    if has_gui():
        for e_id in element_seq.values():
            handles.extend(
                draw_pose(unit_geos[e_id].initial_pb_pose, length=0.02))
            handles.extend(draw_pose(unit_geos[e_id].goal_pb_pose,
                                     length=0.02))
            for e_body in unit_geos[e_id].pybullet_bodies:
                set_pose(e_body, unit_geos[e_id].initial_pb_pose)
        print('pybullet env loaded.')
        # wait_for_user()
        for h in handles:
            remove_debug(h)

    saved_world = WorldSaver()

    ik_fn = ikfast_ur3.get_ik if robot_model == 'ur3' else ikfast_ur5.get_ik
    tot_traj, graph_sizes = \
    direct_ladder_graph_solve_picknplace(pb_robot, ik_joint_names, base_link_name, ee_link_name, ik_fn,
        unit_geos, element_seq, static_obstacles_from_name,
        from_seq_id=from_seq_id, to_seq_id=to_seq_id,
        pick_from_same_rack=pick_from_same_rack,
        tcp_transf=pb_pose_from_Transformation(tcp_tf),
        ee_attachs=ee_attachs, disabled_collision_link_names=disabled_link_names, viz=view_ikfast, st_conf=robot_start_conf,
        num_cart_steps=num_cart_steps)

    picknplace_cart_plans = divide_nested_list_chunks(tot_traj, graph_sizes)

    saved_world.restore()
    print('Cartesian planning finished.')

    # reset robot and parts for better visualization
    set_joint_positions(pb_robot, pb_ik_joints, robot_start_conf)
    for ee in ee_attachs:
        ee.assign()
    for e_id in element_seq.values():
        for e_body in unit_geos[e_id].pybullet_bodies:
            set_pose(e_body, unit_geos[e_id].initial_pb_pose)

    def flatten_unit_geos_bodies(in_dict):
        out_list = []
        for ug in in_dict.values():
            out_list.extend(ug.pybullet_bodies)
        return out_list

    if plan_transit:
        print('Transition planning started.')
        disabled_collision_links = [(link_from_name(pb_robot, pair[0]), link_from_name(pb_robot, pair[1])) \
                for pair in disabled_link_names]

        for seq_id in range(0, from_seq_id):
            e_id = element_seq[seq_id]
            for e_body in unit_geos[e_id].pybullet_bodies:
                set_pose(e_body, unit_geos[e_id].goal_pb_pose)

        for seq_id in range(from_seq_id, to_seq_id + 1):
            e_id = element_seq[seq_id]
            print('----\ntransition seq#{} element #{}'.format(seq_id, e_id))

            if seq_id != from_seq_id:
                tr_start_conf = picknplace_cart_plans[
                    seq_id - 1 - from_seq_id]['place_retreat'][-1]
            else:
                tr_start_conf = robot_start_conf

            place2pick_st_conf = list(tr_start_conf)
            assert picknplace_cart_plans[seq_id - from_seq_id][
                'pick_approach'], 'pick approach not found in sequence {} (element id: {})!'.format(
                    seq_id, e_id)
            place2pick_goal_conf = list(
                picknplace_cart_plans[seq_id -
                                      from_seq_id]['pick_approach'][0])

            saved_world = WorldSaver()

            set_joint_positions(pb_robot, pb_ik_joints, place2pick_st_conf)
            for ee_a in ee_attachs:
                ee_a.assign()

            built_obstacles = []
            ignored_pairs = []
            if pick_from_same_rack:
                built_obstacles =  flatten_unit_geos_bodies({element_seq[prev_seq_id] : \
                    unit_geos[element_seq[prev_seq_id]] for prev_seq_id in range(seq_id)})
                # if seq_id > 0:
                #     ignored_pairs = list(product([ee_attach.child for ee_attach in ee_attachs], unit_geos[element_seq[seq_id-1]].pybullet_bodies))
            else:
                built_obstacles = flatten_unit_geos_bodies(unit_geos)
            place2pick_obstacles = list(
                static_obstacles_from_name.values()) + built_obstacles

            place2pick_path = plan_joint_motion(
                pb_robot,
                pb_ik_joints,
                place2pick_goal_conf,
                attachments=ee_attachs,
                obstacles=place2pick_obstacles,
                disabled_collisions=disabled_collision_links,
                self_collisions=True,
                resolutions=[transit_res] * len(pb_ik_joints),
                restarts=RRT_RESTARTS,
                iterations=RRT_ITERATIONS,
                ignored_pairs=ignored_pairs)
            saved_world.restore()

            if not place2pick_path:
                saved_world = WorldSaver()

                print('****\nseq #{} cannot find place2pick transition'.format(
                    seq_id))
                print('Diagnosis...')

                cfn = get_collision_fn(pb_robot, pb_ik_joints, \
                    obstacles=place2pick_obstacles,
                    attachments=ee_attachs, self_collisions=True, diagnosis=True)

                print('start pose:')
                cfn(place2pick_st_conf)

                print('end pose:')
                cfn(place2pick_goal_conf)

                saved_world.restore()
                print('Diagnosis over')

            assert picknplace_cart_plans[seq_id - from_seq_id][
                'pick_retreat'], 'pick retreat not found! in sequence {} (element id: {})!'.format(
                    seq_id, e_id)
            assert picknplace_cart_plans[seq_id - from_seq_id][
                'place_approach'], 'place approach not found! in sequence {} (element id: {})!'.format(
                    seq_id, e_id)
            pick2place_st_conf = picknplace_cart_plans[
                seq_id - from_seq_id]['pick_retreat'][-1]
            pick2place_goal_conf = picknplace_cart_plans[
                seq_id - from_seq_id]['place_approach'][0]

            saved_world = WorldSaver()

            # create attachement without needing to keep track of grasp...
            set_joint_positions(
                pb_robot, pb_ik_joints,
                picknplace_cart_plans[seq_id - from_seq_id]['pick_retreat'][0])
            # attachs = [Attachment(robot, tool_link, invert(grasp.attach), e_body) for e_body in brick.body]
            element_attachs = [create_attachment(pb_robot, pb_end_effector_link, e_body) \
                for e_body in unit_geos[e_id].pybullet_bodies]

            set_joint_positions(pb_robot, pb_ik_joints, pick2place_st_conf)
            for ee_a in ee_attachs:
                ee_a.assign()
            for e_a in element_attachs:
                e_a.assign()

            built_obstacles = []
            if pick_from_same_rack:
                built_obstacles =  flatten_unit_geos_bodies({element_seq[prev_seq_id] : \
                    unit_geos[element_seq[prev_seq_id]] for prev_seq_id in range(seq_id)})
            else:
                built_obstacles = flatten_unit_geos_bodies(unit_geos)
            pick2place_obstacles = list(
                static_obstacles_from_name.values()) + built_obstacles

            pick2place_path = plan_joint_motion(
                pb_robot,
                pb_ik_joints,
                pick2place_goal_conf,
                disabled_collisions=disabled_collision_links,
                obstacles=pick2place_obstacles,
                attachments=ee_attachs + element_attachs,
                self_collisions=True,
                resolutions=[transit_res] * len(pb_ik_joints),
                restarts=RRT_RESTARTS,
                iterations=RRT_ITERATIONS,
            )

            saved_world.restore()

            if not pick2place_path:
                saved_world = WorldSaver()

                print('****\nseq #{} cannot find pick2place transition'.format(
                    seq_id))
                print('Diagnosis...')

                cfn = get_collision_fn(pb_robot, pb_ik_joints,
                    obstacles=pick2place_obstacles, \
                    attachments=ee_attachs + element_attachs, self_collisions=True, diagnosis=True)

                print('start pose:')
                cfn(pick2place_st_conf)

                print('end pose:')
                cfn(pick2place_goal_conf)

                saved_world.restore()

                print('Diagnosis over')

            picknplace_cart_plans[seq_id -
                                  from_seq_id]['place2pick'] = place2pick_path
            picknplace_cart_plans[seq_id -
                                  from_seq_id]['pick2place'] = pick2place_path

            for e_body in unit_geos[e_id].pybullet_bodies:
                set_pose(e_body, unit_geos[e_id].goal_pb_pose)

            if seq_id == to_seq_id:
                saved_world = WorldSaver()
                return2idle_st_conf = picknplace_cart_plans[
                    seq_id - from_seq_id]['place_retreat'][-1]
                return2idle_goal_conf = robot_start_conf

                set_joint_positions(pb_robot, pb_ik_joints,
                                    return2idle_st_conf)
                for ee_a in ee_attachs:
                    ee_a.assign()

                built_obstacles =  flatten_unit_geos_bodies({element_seq[prev_seq_id] : \
                    unit_geos[element_seq[prev_seq_id]] for prev_seq_id in range(seq_id+1)})
                return2idle_obstacles = list(
                    static_obstacles_from_name.values()) + built_obstacles
                return2idle_path = plan_joint_motion(
                    pb_robot,
                    pb_ik_joints,
                    return2idle_goal_conf,
                    disabled_collisions=disabled_collision_links,
                    obstacles=return2idle_obstacles,
                    attachments=ee_attachs,
                    self_collisions=True,
                    resolutions=[transit_res] * len(pb_ik_joints),
                    restarts=RRT_RESTARTS,
                    iterations=RRT_ITERATIONS,
                )

                if not return2idle_path:
                    saved_world = WorldSaver()

                    print('****\nseq #{} cannot find return2idle transition'.
                          format(seq_id))
                    print('Diagnosis...')

                    cfn = get_collision_fn(pb_robot, pb_ik_joints, \
                        obstacles=return2idle_obstacles,
                        attachments=ee_attachs, self_collisions=True, diagnosis=True)

                    print('start pose:')
                    cfn(return2idle_st_conf)

                    print('end pose:')
                    cfn(return2idle_goal_conf)

                    saved_world.restore()
                    print('Diagnosis over')

                saved_world.restore()
                picknplace_cart_plans[
                    seq_id - from_seq_id]['return2idle'] = return2idle_path

        print('Transition planning finished.')

    # convert to ros JointTrajectory
    traj_json_data = []
    traj_time_count = 0.0
    for i, element_process in enumerate(picknplace_cart_plans):
        e_proc_data = {}
        for sub_proc_name, sub_process in element_process.items():
            sub_process_jt_traj_list = []
            if not sub_process:
                continue
            for jt_sol in sub_process:
                sub_process_jt_traj_list.append(
                    JointTrajectoryPoint(values=jt_sol,
                                         types=[0] * 6,
                                         time_from_start=Duration(
                                             traj_time_count, 0)))
                traj_time_count += 1.0  # meaningless timestamp
            e_proc_data[sub_proc_name] = JointTrajectory(
                trajectory_points=sub_process_jt_traj_list,
                start_configuration=sub_process_jt_traj_list[0]).to_data()
        traj_json_data.append(e_proc_data)

    if result_save_path:
        if not os.path.exists(os.path.dirname(result_save_path)):
            os.mkdir(os.path.dirname(result_save_path))
        with open(result_save_path, 'w+') as outfile:
            json.dump(traj_json_data, outfile)
            print('planned trajectories saved to {}'.format(result_save_path))

    print('\n*************************\nplanning completed.')

    if sim_traj and has_gui():
        #     if has_gui():
        #         wait_for_user()

        for e_id in element_seq.values():
            for e_body in unit_geos[e_id].pybullet_bodies:
                set_pose(e_body, unit_geos[e_id].initial_pb_pose)

        display_picknplace_trajectories(pb_robot, ik_joint_names, ee_link_name,
                                        unit_geos, traj_json_data, \
                                        element_seq=element_seq,
                                        from_seq_id=from_seq_id, to_seq_id=to_seq_id,
                                        ee_attachs=ee_attachs,
                                        cartesian_time_step=cart_ts,
                                        transition_time_step=trans_ts, step_sim=step_sim, per_conf_step=per_conf_step)

    return traj_json_data
예제 #14
0
import compas_fab
from compas_fab.robots import *
from compas_fab.robots import rfl
from compas_fab.backends import VrepClient

# Configure logging to DEBUG to see detailed timing of the path planning
logging.basicConfig(level=logging.DEBUG)

# Configure parameters for path planning
start_pose = Frame((7.453, 2.905, 0.679), (1, 0, 0), (0, -1, 0))
goal_pose = Frame((5.510, 5.900, 1.810), (0, 0, -1), (0, 1, 0))
planner_id = 'rrtconnect'
max_trials = 1
resolution = 0.02
building_member = Mesh.from_obj(
    compas_fab.get('planning_scene/timber_beam.obj'))
structure = [
    Mesh.from_obj(compas_fab.get('planning_scene/timber_structure.obj'))
]
metric = [0.1] * 9
fast_search = True

with VrepClient(debug=True) as client:
    robot = rfl.Robot('A', client=client)
    client.planner.pick_building_member(robot, building_member, start_pose)
    group = robot.model.attr['index']

    path = client.plan_motion(robot,
                              goal_pose,
                              group=group,
                              options={
예제 #15
0
import compas
from compas.robots import LocalPackageMeshLoader
from compas.robots import RobotModel

import compas_fab

# Set high precision to import meshes defined in meters
compas.PRECISION = '12f'

# Locate the URDF file inside compas fab installation
urdf = compas_fab.get('universal_robot/ur_description/urdf/ur5.urdf')

# Create robot model from URDF
model = RobotModel.from_urdf_file(urdf)

# Also load geometry
loader = LocalPackageMeshLoader(compas_fab.get('universal_robot'),
                                'ur_description')
model.load_geometry(loader)

print(model)
예제 #16
0
import time

from compas.datastructures import Mesh

import compas_fab
from compas_fab.backends import RosClient
from compas_fab.robots import CollisionMesh
from compas_fab.robots import PlanningScene

with RosClient() as client:
    robot = client.load_robot()
    scene = PlanningScene(robot)
    assert robot.name == 'ur5'

    # create collision object
    mesh = Mesh.from_stl(compas_fab.get('planning_scene/cone.stl'))
    cm = CollisionMesh(mesh, 'tip')

    # attach it to the end-effector
    group = robot.main_group_name
    scene.attach_collision_mesh_to_robot_end_effector(cm, group=group)

    # sleep a bit before removing the tip
    time.sleep(1)

    scene.reset()
def test_ikfast_inverse_kinematics():
    urdf_filename = compas_fab.get('universal_robot/ur_description/urdf/ur5.urdf')
    srdf_filename = compas_fab.get('universal_robot/ur5_moveit_config/config/ur5.srdf')
    urdf_pkg_name = 'ur_description'

    model = RobotModel.from_urdf_file(urdf_filename)
    semantics = RobotSemantics.from_srdf_file(srdf_filename, model)
    robot = RobotClass(model, semantics=semantics)

    base_link_name = robot.get_base_link_name()
    ik_joint_names = robot.get_configurable_joint_names()
    ik_tool_link_name = robot.get_end_effector_link_name()

    connect(use_gui=False)
    pb_robot = create_pb_robot_from_ros_urdf(urdf_filename, urdf_pkg_name)
    pb_ik_joints = joints_from_names(pb_robot, ik_joint_names)

    max_attempts = 20
    EPS = 1e-3
    sample_fn = get_sample_fn(pb_robot, pb_ik_joints)

    for i in range(max_attempts):
        # randomly sample within joint limits
        conf = sample_fn()
        # sanity joint limit violation check
        assert not violates_limits(pb_robot, pb_ik_joints, conf)

        # ikfast's FK
        fk_fn = ikfast_ur5.get_fk
        ikfast_FK_pb_pose = get_ik_tool_link_pose(fk_fn, pb_robot, ik_joint_names, base_link_name, conf)

        if has_gui():
            print('test round #{}: ground truth conf: {}'.format(i, conf))
            handles = draw_pose(ikfast_FK_pb_pose, length=0.04)
            set_joint_positions(pb_robot, pb_ik_joints, conf)
            wait_for_user()

        # ikfast's IK
        ik_fn = ikfast_ur5.get_ik
        ik_sols = sample_tool_ik(ik_fn, pb_robot, ik_joint_names, base_link_name,
                        ikfast_FK_pb_pose, get_all=True)

        # TODO: UR robot or in general joint w/ domain over 4 pi
        # needs specialized distance function
        q_selected = sample_tool_ik(ik_fn, pb_robot, ik_joint_names, base_link_name,
                        ikfast_FK_pb_pose, nearby_conf=True)
        qsol = best_sol(ik_sols, conf, [1.]*6)
        print('q selected: {}'.format(q_selected))
        print('q best: {}'.format(qsol))

        if has_gui():
            set_joint_positions(pb_robot, pb_ik_joints, qsol)
            wait_for_user()
            for h in handles : remove_debug(h)

        if qsol is None:
            qsol = [999.]*6
        diff = np.sum(np.abs(np.array(qsol) - np.array(conf)))
        if diff > EPS:
            print(np.array(ik_sols))
            print('Best q:{}'.format(qsol))
            print('Actual:{}'.format(np.array(conf)))
            print('Diff:  {}'.format(conf - qsol))
            print('Difdiv:{}'.format((conf - qsol)/np.pi))
            assert False