nbv_sim/policies.py
2021-07-07 10:16:12 +02:00

135 lines
4.2 KiB
Python

import cv_bridge
import numpy as np
from pathlib import Path
import rospy
import sensor_msgs.msg
from visualization_msgs.msg import Marker, MarkerArray
from robot_utils.perception import Image
from robot_utils.ros import tf
from robot_utils.ros.conversions import *
from robot_utils.ros.rviz import *
from robot_utils.spatial import Transform
from vgn.detection import VGN, compute_grasps
from vgn.perception import UniformTSDFVolume
import vgn.vis
def get_policy(name):
if name == "single-view":
return SingleViewBaseline()
else:
raise ValueError("{} policy does not exist.".format(name))
class BasePolicy:
def __init__(self):
self.cv_bridge = cv_bridge.CvBridge()
self.tsdf = UniformTSDFVolume(0.3, 40)
self.vgn = VGN(Path(rospy.get_param("vgn/model")))
self.load_parameters()
self.lookup_transforms()
self.connect_to_camera()
self.connect_to_rviz()
def load_parameters(self):
self.base_frame = rospy.get_param("~base_frame_id")
self.task_frame = rospy.get_param("~frame_id")
self.cam_frame = rospy.get_param("~camera/frame_id")
self.info_topic = rospy.get_param("~camera/info_topic")
self.depth_topic = rospy.get_param("~camera/depth_topic")
def lookup_transforms(self):
tf._init_listener()
rospy.sleep(1.0) # wait to receive transforms
self.T_B_task = tf.lookup(self.base_frame, self.task_frame)
def connect_to_camera(self):
msg = rospy.wait_for_message(
self.info_topic, sensor_msgs.msg.CameraInfo, rospy.Duration(2.0)
)
self.intrinsic = from_camera_info_msg(msg)
rospy.Subscriber(
self.depth_topic, sensor_msgs.msg.Image, self.sensor_cb, queue_size=1
)
def sensor_cb(self, msg):
self.img = Image(depth=self.cv_bridge.imgmsg_to_cv2(msg).astype(np.float32))
self.extrinsic = tf.lookup(
self.cam_frame,
self.task_frame,
msg.header.stamp,
rospy.Duration(0.2),
)
def connect_to_rviz(self):
self.path_pub = rospy.Publisher("path", MarkerArray, queue_size=1, latch=True)
def activate(self):
self.viewpoints = []
self.done = False
self.best_grasp = None # grasp pose defined w.r.t. the robot's base frame
def update(self):
raise NotImplementedError
def integrate_latest_image(self):
self.viewpoints.append(self.extrinsic.inv())
self.tsdf.integrate(
self.img,
self.intrinsic,
self.extrinsic,
)
def predict_best_grasp(self):
tsdf_grid = self.tsdf.get_grid()
out = self.vgn.predict(tsdf_grid)
score_fn = lambda g: g.pose.translation[2]
grasps = compute_grasps(self.tsdf.voxel_size, out, score_fn)
vgn.vis.draw_grasps(grasps, 0.05)
return self.T_B_task * grasps[0].pose if len(grasps) > 0 else None
def draw_scene_cloud(self):
cloud = self.tsdf.get_scene_cloud()
vgn.vis.draw_points(np.asarray(cloud.points))
def draw_camera_path(self):
identity = Transform.identity()
color = np.r_[31, 119, 180] / 255.0
# Spheres for each viewpoint
scale = 0.01 * np.ones(3)
spheres = create_marker(
Marker.SPHERE_LIST, self.task_frame, identity, scale, color
)
spheres.id = 0
spheres.points = [to_point_msg(p.translation) for p in self.viewpoints]
# Line strip connecting viewpoints
scale = [0.005, 0.0, 0.0]
lines = create_marker(
Marker.LINE_STRIP, self.task_frame, identity, scale, color
)
lines.id = 1
lines.points = [to_point_msg(p.translation) for p in self.viewpoints]
self.path_pub.publish(MarkerArray([spheres, lines]))
class SingleViewBaseline(BasePolicy):
"""
Process a single image from the initial viewpoint.
"""
def __init__(self):
super().__init__()
self.rate = 1
def update(self):
self.integrate_latest_image()
self.draw_scene_cloud()
self.draw_camera_path()
self.best_grasp = self.predict_best_grasp()
self.done = True