File size: 5,650 Bytes
e50eb02
 
 
 
 
 
 
 
 
 
 
 
 
fc60903
 
 
 
 
e50eb02
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2be73c4
e50eb02
 
 
 
 
 
 
 
 
 
2be73c4
e50eb02
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2be73c4
e50eb02
 
 
 
 
 
fc60903
e50eb02
 
fc60903
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
import argparse
import numpy as np
import pinocchio as pin
import rerun as rr
import trimesh

class RerunURDF():
    def __init__(self, robot_type):
        self.name = robot_type
        match robot_type:
            case 'g1':
                self.robot = pin.RobotWrapper.BuildFromURDF('robot_description/g1/g1_29dof_rev_1_0.urdf', 'robot_description/g1', pin.JointModelFreeFlyer())
                self.Tpose = np.array([0,0,0.785,0,0,0,1,
                                       -0.15,0,0,0.3,-0.15,0,
                                       -0.15,0,0,0.3,-0.15,0,
                                       0,0,0,
                                       0, 1.57,0,1.57,0,0,0,
                                       0,-1.57,0,1.57,0,0,0]).astype(np.float32)
            case 'h1_2':
                self.robot = pin.RobotWrapper.BuildFromURDF('robot_description/h1_2/h1_2_wo_hand.urdf', 'robot_description/h1_2', pin.JointModelFreeFlyer())
                assert self.robot.model.nq == 7 + 12+1+14
                self.Tpose = np.array([0,0,1.02,0,0,0,1,
                                       0,-0.15,0,0.3,-0.15,0,
                                       0,-0.15,0,0.3,-0.15,0,
                                       0,
                                       0, 1.57,0,1.57,0,0,0,
                                       0,-1.57,0,1.57,0,0,0]).astype(np.float32)
            case 'h1':
                self.robot = pin.RobotWrapper.BuildFromURDF('robot_description/h1/h1.urdf', 'robot_description/h1', pin.JointModelFreeFlyer())
                assert self.robot.model.nq == 7 + 10+1+8
                self.Tpose = np.array([0,0,1.03,0,0,0,1,
                                       0,0,-0.15,0.3,-0.15,
                                       0,0,-0.15,0.3,-0.15,
                                       0,
                                       0, 1.57,0,1.57,
                                       0,-1.57,0,1.57]).astype(np.float32)
            case _:
                print(robot_type)
                raise ValueError('Invalid robot type')
        
        # print all joints names
        # for i in range(self.robot.model.njoints):
        #     print(self.robot.model.names[i])
        
        self.link2mesh = self.get_link2mesh()
        self.load_visual_mesh()
        self.update()
    
    def get_link2mesh(self):
        link2mesh = {}
        for visual in self.robot.visual_model.geometryObjects:
            mesh = trimesh.load_mesh(visual.meshPath)
            name = visual.name[:-2]
            mesh.visual = trimesh.visual.ColorVisuals()
            mesh.visual.vertex_colors = visual.meshColor
            link2mesh[name] = mesh
        return link2mesh
   
    def load_visual_mesh(self):       
        self.robot.framesForwardKinematics(pin.neutral(self.robot.model))
        for visual in self.robot.visual_model.geometryObjects:
            frame_name = visual.name[:-2]
            mesh = self.link2mesh[frame_name]
            
            frame_id = self.robot.model.getFrameId(frame_name)
            parent_joint_id = self.robot.model.frames[frame_id].parentJoint
            parent_joint_name = self.robot.model.names[parent_joint_id]
            frame_tf = self.robot.data.oMf[frame_id]
            joint_tf = self.robot.data.oMi[parent_joint_id]
            rr.log(f'urdf_{self.name}/{parent_joint_name}',
                   rr.Transform3D(translation=joint_tf.translation,
                                  mat3x3=joint_tf.rotation,
                                  axis_length=0.01))
            
            relative_tf = joint_tf.inverse() * frame_tf
            mesh.apply_transform(relative_tf.homogeneous)
            rr.log(f'urdf_{self.name}/{parent_joint_name}/{frame_name}',
                   rr.Mesh3D(
                       vertex_positions=mesh.vertices,
                       triangle_indices=mesh.faces,
                       vertex_normals=mesh.vertex_normals,
                       vertex_colors=mesh.visual.vertex_colors,
                       albedo_texture=None,
                       vertex_texcoords=None,
                   ),
                   static=True)
    
    def update(self, configuration = None):
        self.robot.framesForwardKinematics(self.Tpose if configuration is None else configuration)
        for visual in self.robot.visual_model.geometryObjects:
            frame_name = visual.name[:-2]
            frame_id = self.robot.model.getFrameId(frame_name)
            parent_joint_id = self.robot.model.frames[frame_id].parentJoint
            parent_joint_name = self.robot.model.names[parent_joint_id]
            joint_tf = self.robot.data.oMi[parent_joint_id]
            rr.log(f'urdf_{self.name}/{parent_joint_name}',
                   rr.Transform3D(translation=joint_tf.translation,
                                  mat3x3=joint_tf.rotation,
                                  axis_length=0.01))


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument('--file_name', type=str, help="File name", default='dance1_subject2')
    parser.add_argument('--robot_type', type=str, help="Robot type", default='g1')
    args = parser.parse_args()

    rr.init('Reviz', spawn=True)
    rr.log('', rr.ViewCoordinates.RIGHT_HAND_Z_UP, static=True)

    file_name = args.file_name
    robot_type = args.robot_type
    csv_files = robot_type + '/' + file_name + '.csv'
    data = np.genfromtxt(csv_files, delimiter=',')

    rerun_urdf = RerunURDF(robot_type)
    for frame_nr in range(data.shape[0]):
        rr.set_time_sequence('frame_nr', frame_nr)
        configuration = data[frame_nr, :]
        rerun_urdf.update(configuration)