149 lines
4.9 KiB
Python
149 lines
4.9 KiB
Python
import numpy as np
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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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from .visualization import Visualizer
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from robot_helpers.ros import tf
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from robot_helpers.ros.conversions import *
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from vgn.detection import *
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from vgn.perception import UniformTSDFVolume
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from vgn.utils import *
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class Policy:
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def __init__(self, rate=5):
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self.rate = rate
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self.load_parameters()
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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("~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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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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def init_visualizer(self):
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self.vis = Visualizer()
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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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def calibrate_task_frame(self):
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self.center = 0.5 * (self.bbox.min + self.bbox.max)
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self.T_base_task = Transform.translation(self.center - np.full(3, 0.15))
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self.T_task_base = self.T_base_task.inv()
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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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kp = 4.0
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linear = kp * linear
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scale = np.linalg.norm(linear)
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linear *= np.clip(scale, 0.0, self.linear_vel) / scale
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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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for grasp in in_grasps:
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pose = self.T_base_task * grasp.pose
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tip = pose.rotation.apply([0, 0, 0.05]) + pose.translation
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if self.bbox.is_inside(tip):
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grasp.pose = pose
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grasps.append(grasp)
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scores.append(self.score_fn(grasp))
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grasps, scores = np.asarray(grasps), np.asarray(scores)
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indices = np.argsort(-scores)
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return grasps[indices], scores[indices]
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def score_fn(self, grasp):
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return grasp.quality
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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, x):
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linear, angular = self.compute_error(self.x_d, x)
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if np.linalg.norm(linear) < 0.02:
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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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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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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=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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self.best_grasp = grasps[0] if len(grasps) > 0 else None
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self.done = True
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return np.zeros(6)
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else:
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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, 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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self.vis.path(self.base_frame, self.views)
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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=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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self.best_grasp = grasps[0]
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self.vis.best_grasp(self.base_frame, grasps[0], scores[0])
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self.vis.grasps(self.base_frame, grasps, scores)
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registry = {}
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def register(id, cls):
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global registry
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registry[id] = cls
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def make(id, *args, **kwargs):
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if id in registry:
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return registry[id](*args, **kwargs)
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else:
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raise ValueError("{} policy does not exist.".format(id))
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