Switch to velocity control
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81588a1075
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@ -7,48 +7,50 @@ from vgn.utils import look_at
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class InitialView(SingleViewPolicy):
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def update(self, img, extrinsic):
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self.target = extrinsic
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super().update(img, extrinsic)
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def update(self, img, pose):
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self.x_d = pose
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super().update(img, pose)
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class TopView(SingleViewPolicy):
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def activate(self, bbox):
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super().activate(bbox)
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eye = np.r_[self.center[:2], self.center[2] + 0.3]
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eye = np.r_[self.center[:2], self.center[2] + self.min_z_dist]
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up = np.r_[1.0, 0.0, 0.0]
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self.target = look_at(eye, self.center, up)
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self.x_d = look_at(eye, self.center, up)
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class TopTrajectory(MultiViewPolicy):
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def activate(self, bbox):
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super().activate(bbox)
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eye = np.r_[self.center[:2], self.center[2] + 0.3]
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eye = np.r_[self.center[:2], self.center[2] + self.min_z_dist]
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up = np.r_[1.0, 0.0, 0.0]
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self.target = look_at(eye, self.center, up)
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self.x_d = look_at(eye, self.center, up)
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def update(self, img, extrinsic):
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self.integrate(img, extrinsic)
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if np.linalg.norm(extrinsic.translation - self.target.translation) < 0.01:
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def update(self, img, x):
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self.integrate(img, x)
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linear, angular = self.compute_error(self.x_d, x)
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if np.linalg.norm(linear) < 0.01:
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self.done = True
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else:
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return self.target
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return self.compute_velocity_cmd(linear, angular)
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class CircularTrajectory(MultiViewPolicy):
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def __init__(self, rate):
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super().__init__(rate)
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self.r = 0.1
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self.h = 0.3
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self.duration = 12.0
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self.m = scipy.interpolate.interp1d([0, self.duration], [np.pi, 3.0 * np.pi])
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self.h = self.min_z_dist
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self.duration = 2.0 * np.pi * self.r / self.linear_vel + 2.0
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self.m = scipy.interpolate.interp1d([0.0, self.duration], [np.pi, 3.0 * np.pi])
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def activate(self, bbox):
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super().activate(bbox)
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self.tic = rospy.Time.now()
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def update(self, img, extrinsic):
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self.integrate(img, extrinsic)
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def update(self, img, x):
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self.integrate(img, x)
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elapsed_time = (rospy.Time.now() - self.tic).to_sec()
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if elapsed_time > self.duration:
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self.done = True
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@ -56,4 +58,6 @@ class CircularTrajectory(MultiViewPolicy):
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t = self.m(elapsed_time)
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eye = self.center + np.r_[self.r * np.cos(t), self.r * np.sin(t), self.h]
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up = np.r_[1.0, 0.0, 0.0]
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return look_at(eye, self.center, up)
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x_d = look_at(eye, self.center, up)
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linear, angular = self.compute_error(x_d, x)
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return self.compute_velocity_cmd(linear, angular)
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@ -1,6 +1,6 @@
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import copy
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import cv_bridge
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from geometry_msgs.msg import PoseStamped
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from geometry_msgs.msg import Twist
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import numpy as np
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import rospy
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from sensor_msgs.msg import Image
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@ -35,13 +35,9 @@ class GraspController:
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self.T_ee_cam = tf.lookup(self.ee_frame, self.cam_frame)
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def init_robot_connection(self):
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self.target_pose_pub = rospy.Publisher("command", PoseStamped, queue_size=10)
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self.cartesian_vel_pub = rospy.Publisher("command", Twist, queue_size=10)
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self.gripper = PandaGripperClient()
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def send_cmd(self, pose):
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msg = to_pose_stamped_msg(pose, self.base_frame)
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self.target_pose_pub.publish(msg)
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def init_camera_stream(self):
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self.cv_bridge = cv_bridge.CvBridge()
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rospy.Subscriber(self.depth_topic, Image, self.sensor_cb, queue_size=1)
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@ -65,21 +61,23 @@ class GraspController:
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self.policy.activate(bbox)
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r = rospy.Rate(self.policy.rate)
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while True:
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img, extrinsic = self.get_state()
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next_extrinsic = self.policy.update(img, extrinsic)
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img, pose = self.get_state()
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cmd = self.policy.update(img, pose)
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if self.policy.done:
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break
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self.send_cmd((self.T_ee_cam * next_extrinsic).inv())
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r.sleep()
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else:
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self.cartesian_vel_pub.publish(to_twist_msg(cmd))
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r.sleep()
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return self.policy.best_grasp
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def get_state(self):
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msg = copy.deepcopy(self.latest_depth_msg)
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img = self.cv_bridge.imgmsg_to_cv2(msg).astype(np.float32)
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extrinsic = tf.lookup(self.cam_frame, self.base_frame, msg.header.stamp)
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return img, extrinsic
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pose = tf.lookup(self.base_frame, self.cam_frame, msg.header.stamp)
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return img, pose
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def execute_grasp(self, grasp):
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return
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if not grasp:
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return "aborted"
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@ -1,5 +1,4 @@
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import numpy as np
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from numpy.core.fromnumeric import sort
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from sensor_msgs.msg import CameraInfo
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from pathlib import Path
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import rospy
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@ -19,9 +18,13 @@ class Policy:
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self.init_visualizer()
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def load_parameters(self):
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self.base_frame = rospy.get_param("active_grasp/base_frame_id")
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self.base_frame = rospy.get_param("~base_frame_id")
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info_topic = rospy.get_param("~camera/info_topic")
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self.linear_vel = rospy.get_param("~linear_vel")
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self.min_z_dist = rospy.get_param("~camera/min_z_dist")
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self.qual_threshold = rospy.get_param("~qual_threshold")
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self.task_frame = "task"
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info_topic = rospy.get_param("active_grasp/camera/info_topic")
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msg = rospy.wait_for_message(info_topic, CameraInfo, rospy.Duration(2.0))
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self.intrinsic = from_camera_info_msg(msg)
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@ -30,15 +33,11 @@ class Policy:
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def activate(self, bbox):
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self.bbox = bbox
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self.calibrate_task_frame()
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self.vis.clear()
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self.vis.bbox(self.base_frame, bbox)
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self.tsdf = UniformTSDFVolume(0.3, 40)
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self.vgn = VGN(Path(rospy.get_param("vgn/model")))
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self.views = []
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self.best_grasp = None
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self.done = False
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@ -50,6 +49,15 @@ class Policy:
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tf.broadcast(self.T_base_task, self.base_frame, self.task_frame)
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rospy.sleep(0.1)
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def compute_error(self, x_d, x):
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linear = x_d.translation - x.translation
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angular = (x_d.rotation * x.rotation.inv()).as_rotvec()
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return linear, angular
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def compute_velocity_cmd(self, linear, angular):
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linear = linear / np.linalg.norm(linear) * self.linear_vel
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return np.r_[linear, angular]
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def sort_grasps(self, in_grasps):
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# Transforms grasps into base frame, checks whether they lie on the target, and sorts by their score
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grasps, scores = [], []
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@ -68,20 +76,19 @@ class Policy:
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def score_fn(self, grasp):
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return grasp.quality
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# return grasp.pose.translation[2]
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def update(sekf, img, extrinsic):
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def update(self, img, pose):
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raise NotImplementedError
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class SingleViewPolicy(Policy):
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def update(self, img, extrinsic):
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error = extrinsic.translation - self.target.translation
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def update(self, img, x):
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linear, angular = self.compute_error(self.x_d, x)
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if np.linalg.norm(error) < 0.01:
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self.views.append(extrinsic.inv())
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if np.linalg.norm(linear) < 0.01:
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self.views.append(x)
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self.tsdf.integrate(img, self.intrinsic, extrinsic * self.T_base_task)
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self.tsdf.integrate(img, self.intrinsic, x.inv() * self.T_base_task)
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tsdf_grid, voxel_size = self.tsdf.get_grid(), self.tsdf.voxel_size
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self.vis.scene_cloud(self.task_frame, self.tsdf.get_scene_cloud())
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self.vis.map_cloud(self.task_frame, self.tsdf.get_map_cloud())
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@ -89,7 +96,7 @@ class SingleViewPolicy(Policy):
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out = self.vgn.predict(tsdf_grid)
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self.vis.quality(self.task_frame, voxel_size, out.qual)
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grasps = select_grid(voxel_size, out, threshold=0.90)
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grasps = select_grid(voxel_size, out, threshold=self.qual_threshold)
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grasps, scores = self.sort_grasps(grasps)
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self.vis.grasps(self.base_frame, grasps, scores)
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@ -97,13 +104,13 @@ class SingleViewPolicy(Policy):
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self.best_grasp = grasps[0] if len(grasps) > 0 else None
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self.done = True
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else:
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return self.target
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return self.compute_velocity_cmd(linear, angular)
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class MultiViewPolicy(Policy):
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def integrate(self, img, extrinsic):
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self.views.append(extrinsic.inv())
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self.tsdf.integrate(img, self.intrinsic, extrinsic * self.T_base_task)
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def integrate(self, img, x):
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self.views.append(x)
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self.tsdf.integrate(img, self.intrinsic, x.inv() * self.T_base_task)
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self.vis.scene_cloud(self.task_frame, self.tsdf.get_scene_cloud())
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self.vis.map_cloud(self.task_frame, self.tsdf.get_map_cloud())
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@ -112,7 +119,7 @@ class MultiViewPolicy(Policy):
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tsdf_grid, voxel_size = self.tsdf.get_grid(), self.tsdf.voxel_size
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out = self.vgn.predict(tsdf_grid)
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grasps = select_grid(voxel_size, out, threshold=0.90)
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grasps = select_grid(voxel_size, out, threshold=self.qual_threshold)
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grasps, scores = self.sort_grasps(grasps)
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if len(grasps) > 0:
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@ -16,7 +16,6 @@ class Simulation:
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self.find_urdfs()
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self.load_table()
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self.load_robot()
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self.load_controller()
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self.object_uids = []
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def configure_physics_engine(self, gui, rate, sub_step_count):
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@ -52,11 +51,6 @@ class Simulation:
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self.model = Model(self.panda_urdf, self.arm.base_frame, self.arm.ee_frame)
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self.camera = BtCamera(320, 240, 1.047, 0.1, 1.0, self.arm.uid, 11)
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def load_controller(self):
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q, _ = self.arm.get_state()
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x0 = self.model.pose(self.arm.ee_frame, q)
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self.controller = CartesianPoseController(self.model, self.arm.ee_frame, x0)
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def seed(self, seed):
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self.rng = np.random.default_rng(seed)
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@ -84,8 +78,6 @@ class Simulation:
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p.resetJointState(self.arm.uid, i, q_i, 0)
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p.resetJointState(self.arm.uid, 9, 0.04, 0)
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p.resetJointState(self.arm.uid, 10, 0.04, 0)
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x0 = self.model.pose(self.arm.ee_frame, q)
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self.controller.x_d = x0
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def load_object(self, urdf, ori, pos, scale=1.0):
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uid = p.loadURDF(str(urdf), pos, ori.as_quat(), globalScaling=scale)
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@ -139,31 +131,3 @@ class Simulation:
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aabb_min = np.array(aabb_min) - self.T_world_base.translation
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aabb_max = np.array(aabb_max) - self.T_world_base.translation
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return AABBox(aabb_min, aabb_max)
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class CartesianPoseController:
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def __init__(self, model, frame, x0):
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self.model = model
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self.frame = frame
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self.kp = np.ones(6) * 4.0
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self.max_linear_vel = 0.05
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self.max_angular_vel = 1.57
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self.x_d = x0
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def update(self, q):
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x = self.model.pose(self.frame, q)
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error = np.zeros(6)
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error[:3] = self.x_d.translation - x.translation
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error[3:] = (self.x_d.rotation * x.rotation.inv()).as_rotvec()
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dx = self.limit_rate(self.kp * error)
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J_pinv = np.linalg.pinv(self.model.jacobian(self.frame, q))
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cmd = np.dot(J_pinv, dx)
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return cmd
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def limit_rate(self, dx):
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linear, angular = dx[:3], dx[3:]
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linear = np.clip(linear, -self.max_linear_vel, self.max_linear_vel)
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angular = np.clip(angular, -self.max_angular_vel, self.max_angular_vel)
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return np.r_[linear, angular]
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@ -3,14 +3,17 @@ bt_sim:
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cam_noise: True
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calib_error: True
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active_grasp:
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grasp_controller:
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base_frame_id: panda_link0
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ee_frame_id: panda_hand
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ee_grasp_offset: [0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.065]
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linear_vel: 0.1
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qual_threshold: 0.9
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camera:
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frame_id: camera_optical_frame
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info_topic: /camera/depth/camera_info
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depth_topic: /camera/depth/image_raw
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min_z_dist: 0.22
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vgn:
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model: $(find vgn)/assets/models/vgn_conv.pth
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@ -3,7 +3,7 @@
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from actionlib import SimpleActionServer
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import cv_bridge
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from franka_gripper.msg import *
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from geometry_msgs.msg import PoseStamped
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from geometry_msgs.msg import Twist
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import numpy as np
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import rospy
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from sensor_msgs.msg import JointState, Image, CameraInfo
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@ -27,7 +27,7 @@ class BtSimNode:
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self.plugins = [
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PhysicsPlugin(self.sim),
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JointStatePlugin(self.sim.arm, self.sim.gripper),
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ArmControllerPlugin(self.sim.arm, self.sim.controller),
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CartesianVelocityControllerPlugin(self.sim.arm, self.sim.model),
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MoveActionPlugin(self.sim.gripper),
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GraspActionPlugin(self.sim.gripper),
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CameraPlugin(self.sim.camera),
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@ -46,6 +46,7 @@ class BtSimNode:
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plugin.is_running = False
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rospy.sleep(1.0) # TODO replace with a read-write lock
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bbox = self.sim.reset()
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self.plugins[2].dx_d = np.zeros(6)
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res = ResetResponse(to_bbox_msg(bbox))
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for plugin in self.plugins:
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plugin.is_running = True
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@ -109,22 +110,32 @@ class JointStatePlugin(Plugin):
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self.pub.publish(msg)
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class ArmControllerPlugin(Plugin):
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def __init__(self, arm, controller, rate=30):
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class CartesianVelocityControllerPlugin(Plugin):
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def __init__(self, arm, model, rate=30):
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super().__init__(rate)
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self.arm = arm
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self.controller = controller
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rospy.Subscriber("command", PoseStamped, self.target_cb)
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self.model = model
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self.max_linear_vel = 0.1
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self.max_angular_vel = 1.57
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self.dx_d = np.zeros(6)
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rospy.Subscriber("command", Twist, self.target_cb)
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def target_cb(self, msg):
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assert msg.header.frame_id == self.arm.base_frame
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self.controller.x_d = from_pose_msg(msg.pose)
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self.dx_d = from_twist_msg(msg)
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def update(self):
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q, _ = self.arm.get_state()
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cmd = self.controller.update(q)
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dx = self.limit_rate(self.dx_d)
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J_pinv = np.linalg.pinv(self.model.jacobian(q))
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cmd = np.dot(J_pinv, dx)
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self.arm.set_desired_joint_velocities(cmd)
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def limit_rate(self, dx):
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linear, angular = dx[:3], dx[3:]
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linear = np.clip(linear, -self.max_linear_vel, self.max_linear_vel)
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angular = np.clip(angular, -self.max_angular_vel, self.max_angular_vel)
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return np.r_[linear, angular]
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class MoveActionPlugin(Plugin):
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def __init__(self, gripper, rate=10):
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@ -11,7 +11,7 @@ from active_grasp.srv import Seed
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def main():
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rospy.init_node("active_grasp")
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rospy.init_node("grasp_controller")
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parser = create_parser()
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args = parser.parse_args()
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