solved the fucking mysterous bug

This commit is contained in:
0nhc
2024-10-21 11:32:13 -05:00
parent c8f0354550
commit d70e585860
5 changed files with 136 additions and 23 deletions

View File

@@ -12,6 +12,15 @@ import requests
import matplotlib.pyplot as plt
from vgn.grasp import ParallelJawGrasp
import time
from visualization_msgs.msg import Marker, MarkerArray
from geometry_msgs.msg import Pose
import tf
import sensor_msgs.point_cloud2 as pc2
from sensor_msgs.msg import PointCloud2, PointField
import std_msgs.msg
import ros_numpy
class RealTime3DVisualizer:
@@ -192,6 +201,10 @@ class ActivePerceptionSingleViewPolicy(SingleViewPolicy):
self.updated = False
self._base_url = flask_base_url
# For debugging
self.pcd_publisher = rospy.Publisher('/debug_pcd', PointCloud2, queue_size=10)
self.grasp_publisher = rospy.Publisher("/grasp_markers", MarkerArray, queue_size=10)
def request_grasping_pose(self, data):
response = requests.post(f"{self._base_url}/get_gsnet_grasp", json=data)
@@ -247,18 +260,29 @@ class ActivePerceptionSingleViewPolicy(SingleViewPolicy):
self.target_points, self.scene_points = self.depth_image_to_ap_input(img, seg, target_id)
target_points_list = np.asarray(self.target_points.cpu().numpy())[0].tolist()
central_point_of_target = np.mean(target_points_list, axis=0)
target_points_radius = np.max(np.linalg.norm(target_points_list - central_point_of_target, axis=1))
scene_points_list = np.asarray(self.scene_points.cpu().numpy())[0].tolist()
merged_points_list = target_points_list + scene_points_list
# gsnet_input_points = self.crop_pts_sphere(np.asarray(merged_points_list), central_point_of_target)
gsnet_input_points = target_points_list
gsnet_input_points = self.crop_pts_sphere(np.asarray(merged_points_list),
central_point_of_target,
radius=target_points_radius)
# gsnet_input_points = target_points_list
# gsnet_input_points = merged_points_list
self.publish_pointcloud(gsnet_input_points)
gsnet_grasping_poses = np.asarray(self.request_grasping_pose(gsnet_input_points))
# DEBUG: publish grasps
# self.publish_grasps(gsnet_grasping_poses)
# Convert all grasping poses' reference frame to arm frame
current_cam_pose = torch.from_numpy(x.as_matrix()).float().to("cuda:0")
for gg in gsnet_grasping_poses:
T = np.asarray(gg['T'])
gg['T'] = current_cam_pose.cpu().numpy() @ T
gg['T'] = current_cam_pose.cpu().numpy().dot(np.asarray(gg['T']))
# Now here is a mysterous bug, the grasping poses have to be rotated
# 90 degrees around y-axis to be in the correct reference frame
R = np.array([[0, 0, 1], [0, 1, 0], [-1, 0, 0]])
gg['T'][:3, :3] = gg['T'][:3, :3].dot(R)
# Convert grasping poses to ParallelJawGrasp objects
grasps = []
qualities = []
@@ -271,7 +295,6 @@ class ActivePerceptionSingleViewPolicy(SingleViewPolicy):
# Visualize grasps
self.vis.grasps(self.base_frame, grasps, qualities)
time.sleep(1000000)
# Filter grasps
filtered_grasps = []
@@ -280,8 +303,8 @@ class ActivePerceptionSingleViewPolicy(SingleViewPolicy):
pose = grasp.pose
# tip = pose.rotation.apply([0, 0, 0.05]) + pose.translation
tip = pose.translation
# if self.bbox.is_inside(tip):
if(True):
if self.bbox.is_inside(tip):
# if(True):
q_grasp = self.solve_ee_ik(q, pose * self.T_grasp_ee)
if q_grasp is not None:
filtered_grasps.append(grasp)
@@ -294,6 +317,59 @@ class ActivePerceptionSingleViewPolicy(SingleViewPolicy):
self.vis.clear_grasp()
self.done = True
def publish_grasps(self, gg):
marker_array = MarkerArray()
marker_array.markers = []
for idx, g in enumerate(gg):
g['T'] = np.asarray(g['T'])
marker = Marker()
marker.header.frame_id = "camera_depth_optical_frame"
marker.header.stamp = rospy.Time.now()
marker.ns = "grasps"
marker.id = idx
marker.type = Marker.ARROW
marker.action = Marker.ADD
marker.pose.position.x = g['T'][0, 3]
marker.pose.position.y = g['T'][1, 3]
marker.pose.position.z = g['T'][2, 3]
q = tf.transformations.quaternion_from_matrix(g['T'])
marker.pose.orientation.x = q[0]
marker.pose.orientation.y = q[1]
marker.pose.orientation.z = q[2]
marker.pose.orientation.w = q[3]
marker.scale.x = 0.1
marker.scale.y = 0.01
marker.scale.z = 0.01
marker.color.a = 1.0
marker.color.r = 0.0
marker.color.g = 1.0
marker.color.b = 0.0
marker_array.markers.append(marker)
self.grasp_publisher.publish(marker_array)
def publish_pointcloud(self, point_cloud):
point_cloud = np.asarray(point_cloud)
cloud_msg = self.create_pointcloud_msg(point_cloud)
self.pcd_publisher.publish(cloud_msg)
def create_pointcloud_msg(self, point_cloud):
# Define the header
header = std_msgs.msg.Header()
header.stamp = rospy.Time.now()
header.frame_id = 'camera_depth_optical_frame' # Change this to your desired frame of reference
# Define the fields for the PointCloud2 message
fields = [
PointField(name="x", offset=0, datatype=PointField.FLOAT32, count=1),
PointField(name="y", offset=4, datatype=PointField.FLOAT32, count=1),
PointField(name="z", offset=8, datatype=PointField.FLOAT32, count=1),
]
# Create the PointCloud2 message
cloud_msg = pc2.create_cloud(header, fields, point_cloud)
return cloud_msg
def crop_pts_sphere(self, points, crop_center, radius=0.2):
crop_mask = np.linalg.norm(points - crop_center, axis=1) < radius
return points[crop_mask].tolist()