├── LICENSE
├── README.md
├── animation.py
├── constant.py
├── mathematics.py
├── media
├── ik-issue.gif
├── leg_pose1.png
├── leg_pose2.png
├── plt_ani_tripod_gait.gif
├── plt_body_ik.gif
├── plt_ex1_ik.png
├── plt_ex1_initial.png
├── useage-dimension.gif
├── useage-fk.gif
├── useage-gait.gif
└── useage-ik.gif
├── models.py
├── style.ini
└── ui.py
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573 | option of following the terms and conditions either of that numbered
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575 | Foundation. If the Program does not specify a version number of the
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587 | later version.
588 |
589 | 15. Disclaimer of Warranty.
590 |
591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
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612 | 17. Interpretation of Sections 15 and 16.
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621 | END OF TERMS AND CONDITIONS
622 |
623 | How to Apply These Terms to Your New Programs
624 |
625 | If you develop a new program, and you want it to be of the greatest
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628 |
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649 |
650 | Also add information on how to contact you by electronic and paper mail.
651 |
652 | If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
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657 | This is free software, and you are welcome to redistribute it
658 | under certain conditions; type `show c' for details.
659 |
660 | The hypothetical commands `show w' and `show c' should show the appropriate
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667 | .
668 |
669 | The GNU General Public License does not permit incorporating your program
670 | into proprietary programs. If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library. If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License. But first, please read
674 | .
675 |
--------------------------------------------------------------------------------
/README.md:
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1 | # Hexapod Robot Simulator
2 |
3 | A simulator for hexapod **pose** and **gait** control based on *forward* and *inverse* kinematics.
4 |
5 | |Dimension |Forward Kinematics 
6 | --- | ---
7 |
8 | |Inverse Kinematics |Walking Gait 
9 | --- | ---
10 |
11 | This project is implemented by Python with *numpy* for some matrix computations, *scipy.transforms* for 3D transformation, *dash* for user interface and interactive visualization, *matplotlib* for visualization/animation.
12 |
13 | ### Tutorial
14 | A [video tutorial](https://www.bilibili.com/video/BV1qF41167Sx) for building this project from scratch is available from [my channel](https://space.bilibili.com/13031745) on Bilibili (Chinese Language).
15 |
16 | ### How to use
17 | + just run the file `ui.py` and open on your browser, a web app will be hosted on http://127.0.0.1:8050, .
18 | + in `models.py`: you can run several visualizations/testings of the single models.
19 | + **Hexapod**
20 | ```python
21 | if __name__ == "__main__":
22 | hexapod = Hexapod()
23 | fig1, ax1 = hexapod.visualize3d()
24 | hexapod.solve_ik([0, 6, 2], [0, 0, 0.2])
25 | print(hexapod.get_legs_pose())
26 | fig2, ax2 = hexapod.visualize3d()
27 | plt.show()
28 | ```
29 | This will print the leg positions (joint angles of each leg) of the hexapod:
30 | ```python
31 | {'MiddleRight': {'coxa': -92.09547174803812, 'femur': 6.36113571972891, 'tibia': -64.60434061668676}, 'FrontRight': {'coxa': -45.09639870158676, 'femur': 0.09531185287904773, 'tibia': -78.66206919332849}, 'FrontLeft': {'coxa': 45.10012726867826, 'femur': -12.077624233788663, 'tibia': -64.00686346144602}, 'MiddleLeft': {'coxa': 88.11133082594907, 'femur': -18.539795381247323, 'tibia': -49.1551576670496}, 'RearLeft': {'coxa': 130.89088550579493, 'femur': -11.540579859453953, 'tibia': -40.477079527074935}, 'RearRight': {'coxa': -139.3256544041924, 'femur': 0.7673781486253016, 'tibia': -44.45742377675202}}
32 | ```
33 |
34 | Two figures of the hexapod's initial pose and the changed pose will also be displayed:
35 | | | 
36 | --- | ---
37 |
38 | + **Legs**
39 | ```python
40 | if __name__ == "__main__":
41 | leg = Leg(lengths=[2,2,3])
42 | t = get_transformation_homo([0, 0, 45], [0,4,0])
43 | leg.change_pose([-60, 45, 30])
44 | leg.transform(t)
45 | fig, ax = leg.visualize3d()
46 | fig, ax = leg.visualizeAxis(fig=fig, ax=ax, scale=1)
47 | ```
48 | this will display the leg 3D positions and the local axis:
49 |  | 
50 | ---|---
51 | + `animation.py`: run this file to display animation of the hexapod, followings are examples of tripod gait and IK:
52 |  | 
53 | ---|---
54 |
55 | ### Issues
56 | + The angle range of every joint has not been limited, i.e., it can move from 0 to $2\pi$
57 | + In the inverse kinematics page, the solution may be wrong when it exceeds the allowed tilt range like:
58 |
59 |
60 |
61 |
62 | Currently I have yet got an efficient way to address this issue, do you have any good idea?
63 | + Only Tripod gait has been implemented. Other gait will be realized in the [Webots project](https://github.com/XuelongSun/HexapodWebots): a simulated hexapod robot with physics engine.
64 | + Functions of some widgets (like the stance sliders in the IK tab) in the UI are not implemented.
65 |
66 | ---
67 |
68 | > This project is mainly inspired by [Mithi's Bare-Minimum Hexapod Robot Simulator](https://github.com/mithi/hexapod)
69 |
70 | > This project is a good example of `learn by doing`, have fun!
71 |
72 |
73 |
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/animation.py:
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1 | import numpy as np
2 | import matplotlib.pyplot as plt
3 | from mpl_toolkits.mplot3d.art3d import Poly3DCollection
4 | from matplotlib.animation import FuncAnimation
5 | from models import Body, Leg, Hexapod
6 |
7 | fig = plt.figure(figsize=(10,10))
8 | ax = fig.add_subplot(111, projection='3d')
9 |
10 | hexapod = Hexapod([3,2,3])
11 |
12 | # draw body
13 | head = ax.scatter(hexapod.body.head.x,
14 | hexapod.body.head.y,
15 | hexapod.body.head.z,
16 | facecolors='red', edgecolors='tomato', s=hexapod.body.f*80, zorder=1)
17 | v = list([[v.x, v.y, v.z] for v in hexapod.body.vertices])
18 | body = ax.add_collection3d(Poly3DCollection([v], facecolor='w', edgecolor='k', linewidth=8, zorder=0))
19 | # draw legs
20 | legs = {}
21 | for k, leg in hexapod.legs.items():
22 | px = [leg.points_global[i].x for i in range(4)]
23 | py = [leg.points_global[i].y for i in range(4)]
24 | pz = [leg.points_global[i].z for i in range(4)]
25 | l, = ax.plot(px, py, pz, lw=8, color='k',
26 | marker='o', markersize=10, mec='k', mfc='k')
27 | legs[k] = l
28 |
29 | tip_curve, = ax.plot([], [], lw=1, color='r')
30 | tip_curve_counter = 20
31 | tip_leg = 5
32 | tip_p = hexapod.legs[tip_leg].get_ground_contact_point()
33 | tip_points = [[tip_p.x], [tip_p.y], [tip_p.z]]
34 |
35 | t = np.linspace(0, np.pi*2, 100)
36 | rot_x = -10*np.sin(t)
37 | rot_y = -5*np.cos(t)
38 | rot_z = -5*np.sin(t)
39 | # ax.set_axis_off()
40 | hexapod.generate_walking_sequence(dict(
41 | Gait='Tripod', HipSwing=30, LiftSwing=60, StepNum=10, Direction=-1, Rotation=0
42 | ))
43 |
44 | def update(frame):
45 | global tip_points
46 | # IK
47 | hexapod.solve_ik([rot_x[frame%len(t)], rot_y[frame%len(t)], 0], [0, 0, 0])
48 | # Gait
49 | # hexapod.set_pose_from_walking_sequence(frame%len(hexapod.walking_sequence[0]['coxia']))
50 | # update body
51 | v = list([[v.x, v.y, v.z] for v in hexapod.body.vertices])
52 | body.set_verts([v])
53 | # update head
54 | head._offsets3d = ([hexapod.body.head.x], [hexapod.body.head.y], [hexapod.body.head.z])
55 | # update legs
56 | for k, leg in hexapod.legs.items():
57 | px = [leg.points_global[i].x for i in range(4)]
58 | py = [leg.points_global[i].y for i in range(4)]
59 | pz = [leg.points_global[i].z for i in range(4)]
60 | legs[k].set_data(px, py)
61 | legs[k].set_3d_properties(pz)
62 | # update tip curve
63 | tip_p = hexapod.legs[tip_leg].get_ground_contact_point()
64 | if frame == 0:
65 | tip_points = [[tip_p.x], [tip_p.y], [tip_p.z]]
66 | else:
67 | tip_points[0].append(tip_p.x)
68 | tip_points[1].append(tip_p.y)
69 | tip_points[2].append(tip_p.z)
70 | if len(tip_points[0]) < tip_curve_counter:
71 | tip_curve.set_data(tip_points[0], tip_points[1])
72 | tip_curve.set_3d_properties(tip_points[2])
73 | else:
74 | tip_curve.set_data(tip_points[0][-tip_curve_counter:-1],
75 | tip_points[1][-tip_curve_counter:-1])
76 | tip_curve.set_3d_properties(tip_points[2][-tip_curve_counter:-1])
77 |
78 | ax.set_aspect('equal')
79 |
80 | # ani = FuncAnimation(fig, update, frames=4*len(hexapod.walking_sequence[0]['coxia']), interval=20, blit=False)
81 | ani = FuncAnimation(fig, update, frames=4*len(t), interval=20, blit=False)
82 | plt.show()
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/constant.py:
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1 | # useful
2 | AXIS_INDEX = {'X':0, 'Y':1, 'Z':2}
3 |
4 | # hexapod robot
5 | DEFAULT_DIMSIONS = (2, 4, 4)
6 |
7 | # legs
8 | DEFAULT_LEG_LENGTH = (2, 2, 2)
9 | DEFAULT_LEG_ALPHA_BIAS = (-90, -45, 45, 90, 135, -135)
10 | DEFAULT_LEG_GAMMA = -90
11 | LEG_ID_NAMES = {0: "MiddleRight", 1:"FrontRight", 2:"FrontLeft",
12 | 3: "MiddleLeft", 4:"RearLeft", 5:"RearRight"}
13 | LEG_NAMES_ID = {}
14 | for k,v in LEG_ID_NAMES.items():
15 | LEG_NAMES_ID[v] = k
16 | LEG_SEG_ID_NAMES = {0:"coxa", 1:"femur", 2:"tibia"}
17 | LEG_SEG_NAMES_ID = {}
18 | for k, v in LEG_SEG_ID_NAMES.items():
19 | LEG_SEG_NAMES_ID[v] = k
20 |
21 | GOOD_LEG_TRIOS = [
22 | (0, 1, 3),
23 | (0, 1, 4),
24 | (0, 2, 3),
25 | (0, 2, 4),
26 | (0, 2, 5),
27 | (0, 3, 4),
28 | (0, 3, 5),
29 | (1, 2, 4),
30 | (1, 2, 5),
31 | (1, 3, 4),
32 | (1, 3, 5),
33 | (1, 4, 5),
34 | (2, 3, 5),
35 | (2, 4, 5),
36 | ]
37 |
38 | ADJACENT_LEG_TRIOS = [
39 | (0, 1, 2),
40 | (1, 2, 3),
41 | (2, 3, 4),
42 | (3, 4, 5),
43 | (0, 4, 5),
44 | (0, 1, 5),
45 | ]
46 |
47 | LEG_TRIOS = GOOD_LEG_TRIOS + ADJACENT_LEG_TRIOS
48 |
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/mathematics.py:
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1 | import numpy as np
2 | from scipy.spatial.transform import Rotation as R
3 |
4 | def combine_rot_trans_to_homo(rot, trans):
5 | M = np.identity(4)
6 | M[:3, :3] = rot
7 | M[:3, 3] = trans
8 | return M
9 |
10 | def get_transformation_homo(rot, trans, degrees=True):
11 | M = np.identity(4)
12 | M[:3, :3] = R.from_euler("XYZ", rot, degrees=degrees).as_matrix()
13 | # translation
14 | M[:3, 3] = trans
15 | return M
16 |
17 | def get_plane_norm(p0, p1, p2):
18 | '''get the unit vector of the plane's norm given three points
19 | '''
20 | u = p1 - p0
21 | v = p2 - p0
22 | n = np.cross(u, v)
23 | n = n / np.linalg.norm(n)
24 | return n
25 |
26 | def is_point_within_triangle_same_plane(point, triangle):
27 | '''determine if the point is within the triangle formed by three points
28 | point is already in the plane formed defined by the triangle
29 | '''
30 | AB = triangle[1]-triangle[0]
31 | AC = triangle[2]-triangle[0]
32 | PA = point - triangle[0]
33 | PB = point - triangle[1]
34 | PC = point - triangle[2]
35 | area_triangle = np.linalg.norm(np.cross(AB, AC))
36 | alpha = np.linalg.norm(np.cross(PB, PC))/area_triangle
37 | beta = np.linalg.norm(np.cross(PC, PA))/area_triangle
38 | gamma = 1 - alpha - beta
39 | return (0 < alpha < 1) and (0 < beta < 1) and (0 < gamma < 1)
40 |
41 | # https://math.stackexchange.com/questions/544946/determine-if-projection-of-3d-point-onto-plane-is-within-a-triangle
42 | # https://gamedev.stackexchange.com/questions/23743/whats-the-most-efficient-way-to-find-barycentric-coordinates
43 | # https://en.wikipedia.org/wiki/Barycentric_coordinate_system
44 | def is_projected_point_within_triangle(point, triangle):
45 | '''determine if the point is within the triangle formed by three points
46 | by applying the Barycentric coordinates
47 | '''
48 | u = triangle[1]-triangle[0]
49 | v = triangle[2]-triangle[0]
50 | w = point - triangle[0]
51 | n = np.cross(u, v)
52 | alpha = np.linalg.norm(np.cross(u, w).dot(n))/n.dot(n)
53 | beta = np.linalg.norm(np.cross(w, v).dot(n))/n.dot(n)
54 | gamma = 1 - alpha - beta
55 | return (0 < alpha < 1) and (0 < beta < 1) and (0 < gamma < 1)
56 |
57 | # https://stackoverflow.com/questions/45142959/calculate-rotation-matrix-to-align-two-vectors-in-3d-space
58 | # https://math.stackexchange.com/questions/180418/calculate-rotation-matrix-to-align-vector-a-to-vector-b-in-3d
59 | def get_rotation_matrix_align_vectors(vec1, vec2):
60 | """ Find the rotation matrix that aligns vec1 to vec2
61 | :param vec1: A 3d "source" vector
62 | :param vec2: A 3d "destination" vector
63 | :return mat: A transform matrix (3x3) which when applied to vec1, aligns it with vec2.
64 | """
65 | a, b = (vec1 / np.linalg.norm(vec1)).reshape(3), (vec2 / np.linalg.norm(vec2)).reshape(3)
66 | v = np.cross(a, b)
67 | c = np.dot(a, b)
68 | s = np.linalg.norm(v)
69 | if s == 0.0:
70 | return np.eye(3)
71 | kmat = np.array([[0, -v[2], v[1]], [v[2], 0, -v[0]], [-v[1], v[0], 0]])
72 | rotation_matrix = np.eye(3) + kmat + kmat.dot(kmat) * ((1 - c) / (s ** 2))
73 | return rotation_matrix
74 |
75 | # https://www.maplesoft.com/support/help/Maple/view.aspx?path=MathApps%2FProjectionOfVectorOntoPlane
76 | def project_vector_onto_plane(vec, plane_norm):
77 | s = vec.dot(plane_norm) / plane_norm.dot(plane_norm)
78 | return vec - s*plane_norm
79 |
80 | def vector_angle(v1, v2, degree=True):
81 | v = v1.dot(v2)/np.sqrt(v1.dot(v1)*v2.dot(v2))
82 | if abs(v) <= 1:
83 | a = np.arccos(v)
84 | else:
85 | a = 0.0
86 |
87 | return a if not degree else np.rad2deg(a)
88 |
89 | def can_form_triangle(a, b, c):
90 | return (a + b > c) and (a + c > b) and (b + c > a)
91 |
92 | class Point3D:
93 | def __init__(self, x=0, y=0, z=0, name='None') -> None:
94 | self.x = x
95 | self.y = y
96 | self.z = z
97 | self.name = name
98 |
99 | def get_coordinates(self):
100 | return self.x, self.y, self.z
101 |
102 | def set_coordinates(self, coordinates):
103 | if hasattr(coordinates, '__len__'):
104 | if len(coordinates) >= 3:
105 | self.x = coordinates[0]
106 | self.y = coordinates[1]
107 | self.z = coordinates[2]
108 | else:
109 | raise ValueError
110 | else:
111 | raise ValueError
112 |
113 | def get_coordinates_homo(self):
114 | return self.x, self.y, self.z, 1
115 |
116 | def __repr__(self):
117 | s = f"{self.name}:({self.x:>4.2f}, {self.y:>4.2f}, {self.z:>4.2f})"
118 | return s
119 |
120 | def __add__(self, b):
121 | if isinstance(b, Point3D):
122 | return Point3D(self.x + b.x, self.y + b.y, self.z + b.z, name=self.name)
123 | elif isinstance(b, float) or isinstance(b, int):
124 | return Point3D(self.x + b, self.y + b, self.z + b, name=self.name)
125 | elif hasattr(b, "__len__"):
126 | if len(b) == 3:
127 | return Point3D(self.x + b[0], self.y + b[1], self.z + b[2], name=self.name)
128 | else:
129 | raise ValueError
130 |
131 | def __sub__ (self, b):
132 | if isinstance(b, Point3D):
133 | return Point3D(self.x - b.x, self.y - b.y, self.z - b.z, name=self.name + '-' + b.name)
134 | elif isinstance(b, float) or isinstance(b, int):
135 | return Point3D(self.x - b, self.y - b, self.z - b, name=self.name + '-' + str(b))
136 | else:
137 | raise ValueError
138 |
139 | def dot(self, b):
140 | if isinstance(b, Point3D):
141 | return self.x*b.x + self.y*b.y + self.z*b.z
142 | else:
143 | raise ValueError
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/models.py:
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1 | from copy import deepcopy
2 |
3 | import numpy as np
4 | import matplotlib.pyplot as plt
5 | from matplotlib.patches import Polygon
6 | from mpl_toolkits.mplot3d.art3d import Poly3DCollection
7 | from scipy.spatial.transform import Rotation as R
8 |
9 | from constant import *
10 | from mathematics import *
11 |
12 | class Body:
13 | # |-f-|
14 | # P2---*---P1--------
15 | # / | \ |
16 | # / | \ s
17 | # / | \ |
18 | # P3-------------P0 ---
19 | # \ | /|
20 | # \ | / |
21 | # \ | / |
22 | # P4--*--P5 |
23 | # | |
24 | # |---m---|
25 | # y axis
26 | # ^
27 | # |
28 | # |
29 | # ----> x axis
30 | def __init__(self, f=5, s=10, m=10) -> None:
31 | self.init_vertices((f,m,s))
32 |
33 | def init_vertices(self, dim):
34 | self.f, self.s, self.m = dim
35 | self.vertices = [
36 | Point3D(self.m, 0, 0, 'P0'),
37 | Point3D(self.f, self.s, 0, 'P1'),
38 | Point3D(-self.f, self.s, 0, 'P2'),
39 | Point3D(-self.m, 0, 0, 'P3'),
40 | Point3D(-self.f, -self.s, 0, 'P4'),
41 | Point3D(self.f, -self.s, 0, 'P5')
42 | ]
43 | self.cog = Point3D(0, 0, 0, 'COG')
44 | self.head = Point3D(0, self.s, 0, 'Head')
45 |
46 | def translate(self, offset):
47 | if hasattr(offset, "__len__"):
48 | if len(offset) == 3:
49 | for p in self.vertices + [self.cog, self.head]:
50 | p.set_coordinates([p.x + offset[0], p.y + offset[1], p.z + offset[2]])
51 | else:
52 | raise ValueError
53 | else:
54 | raise ValueError
55 |
56 | def rotate(self, rot):
57 | if hasattr(rot, "__len__"):
58 | if len(rot) == 3:
59 | r = R.from_euler('XYZ', rot, degrees=True).as_matrix()
60 | for p in self.vertices + [self.cog, self.head]:
61 | p.set_coordinates(np.matmul(r, p.get_coordinates()))
62 | else:
63 | raise ValueError
64 | else:
65 | raise ValueError
66 |
67 | def transform(self, transform):
68 | for v in self.vertices:
69 | v.set_coordinates(transform.dot(v.get_coordinates_homo()))
70 | self.head.set_coordinates(transform.dot(self.head.get_coordinates_homo()))
71 | self.cog.set_coordinates(transform.dot(self.cog.get_coordinates_homo()))
72 |
73 | def change_dimensions(self, dimension):
74 | self.init_vertices(dimension)
75 |
76 | def visualize2d(self, fig=None, ax=None):
77 | if fig is None:
78 | fig, ax = plt.subplots()
79 | # add head
80 | ax.scatter(self.head.x, self.head.y, facecolors='red', edgecolors='tomato', alpha=0.7, s=self.f*20)
81 | ax.text(self.head.x, self.head.y, 'Head')
82 | # add center of gravity
83 | ax.scatter(self.cog.x, self.cog.y, facecolors='k', edgecolors='gray', alpha=0.7, s=self.f*10)
84 | ax.text(self.cog.x, self.cog.y, 'COG')
85 | # add body hexagon
86 | v = [(v.x, v.y) for v in self.vertices]
87 | body = Polygon(v, facecolor='skyblue', alpha=0.6, fill=True, edgecolor='darkblue')
88 | ax.add_patch(body)
89 | # add point label
90 | for v in self.vertices:
91 | ax.text(v.x, v.y, v.name)
92 |
93 | # adjuestment
94 | ax.set_xlim([self.cog.x-1.5*self.m, self.cog.x + 1.5*self.m])
95 | ax.set_ylim([self.cog.y-1.5*self.s, self.cog.y + 1.5*self.s])
96 | ax.grid()
97 | ax.set_aspect('equalxy')
98 | return fig, ax
99 |
100 | def visualize3d(self, fig=None, ax=None):
101 | if fig is None:
102 | fig = plt.figure()
103 | ax = fig.add_subplot(projection="3d", proj_type="ortho")
104 | # add head
105 | ax.scatter(self.head.x, self.head.y, self.head.z, facecolors='red', edgecolors='tomato', alpha=0.7, s=self.f*20)
106 | ax.text(self.head.x, self.head.y, self.head.z, 'Head')
107 | # add center of gravity
108 | ax.scatter(self.cog.x, self.cog.y, self.cog.z, facecolors='k', edgecolors='gray', alpha=0.7, s=self.f*10)
109 | ax.text(self.cog.x, self.cog.y, self.cog.z, 'COG')
110 | v = list([[v.x, v.y, v.z] for v in self.vertices])
111 | ax.add_collection3d(Poly3DCollection([v], facecolor='skyblue', alpha=0.6, edgecolor='darkblue', linewidth=5))
112 | ax.set_xlim([self.cog.x-1.5*self.m, self.cog.x + 1.5*self.m])
113 | ax.set_ylim([self.cog.y-1.5*self.s, self.cog.y + 1.5*self.s])
114 | ax.set_zlim([-5, 5])
115 | ax.set_aspect('equal')
116 | return fig, ax
117 |
118 |
119 | class Leg:
120 | # |--lengths[0]-|--lengths[1]--|
121 | # |=============|==============| p2 -------
122 | # p0 p1 | |
123 | # (origin) | |
124 | # | lengths[2]
125 | # | |
126 | # | |
127 | # | p3 -------
128 | # z axis
129 | # |
130 | # |
131 | # |------- y axis
132 | # origin
133 | def __init__(self, lengths=[10, 10, 10],
134 | name='none', joint_num=3) -> None:
135 | self.joint_num = joint_num
136 | self.name=name
137 |
138 | self.lengths = lengths
139 | self.angles = [0, 0, 0]
140 | self.reset_pose()
141 | self.reset_transforms()
142 | self.global_transform = np.identity(4)
143 | # limitations of the angels / degrees
144 | self.angle_limits = [(-180, 180), (-180, 180), (-180, 180)]
145 |
146 | def __repr__(self):
147 | s = f"Leg:{self.name}({self.origin})"
148 | return s
149 |
150 | def reset_pose(self):
151 | self.angles = [0, 0, 0]
152 | p0 = Point3D(0, 0, 0, name='P0-BodyContact')
153 | p1 = Point3D(0, self.lengths[0], 0, name='P1-coxa')
154 | p2 = Point3D(0, self.lengths[0] + self.lengths[1], 0, name='P2-femur')
155 | p3 = Point3D(0, self.lengths[0] + self.lengths[1] + self.lengths[2], 0, name='P3-tibia')
156 | self.points_global = [p0, p1, p2, p3]
157 |
158 | def reset_transforms(self):
159 | # axes
160 | t_p0 = get_transformation_homo([0, 0, 0], [0, 0, 0])
161 | t_p1_p0 = get_transformation_homo([0, 0, 0], [0, self.lengths[0], 0])
162 | # t_p1 = np.matmul(t_p0, t_p1_p0)
163 | t_p1 = t_p1_p0.dot(t_p0)
164 | t_p2_p1 = get_transformation_homo([0, 0, 0], [0, self.lengths[1], 0])
165 | # t_p2 = np.matmul(t_p1, t_p2_p1)
166 | t_p2 = t_p2_p1.dot(t_p1)
167 | t_p3_p2 = get_transformation_homo([0, 0, 0], [0, self.lengths[2], 0])
168 | # t_p3 = np.matmul(t_p2, t_p3_p2)
169 | t_p3 = t_p3_p2.dot(t_p2)
170 | self.transforms = [t_p0, t_p1, t_p2, t_p3]
171 | return self.transforms
172 |
173 | def _update_transforms(self):
174 | t_p0 = get_transformation_homo([0, 0, self.angles[0]], [0, 0, 0])
175 | t_p1_p0 = get_transformation_homo([self.angles[1], 0, 0], [0, self.lengths[0], 0])
176 | t_p1 = t_p0.dot(t_p1_p0)
177 | t_p2_p1 = get_transformation_homo([self.angles[2], 0, 0], [0, self.lengths[1], 0])
178 | t_p2 = t_p1.dot(t_p2_p1)
179 | t_p3_p2 = get_transformation_homo([0, 0, 0], [0, self.lengths[2], 0])
180 | t_p3 = t_p2.dot(t_p3_p2)
181 | self.transforms = [t_p0, t_p1, t_p2, t_p3]
182 |
183 | def _update_pose(self):
184 | for p, t in zip(self.points_global, self.transforms):
185 | p.set_coordinates(self.global_transform.dot(t.dot([0, 0, 0, 1])))
186 | p.name = 'BodyCOG-' + p.name
187 |
188 | def change_pose(self, angles):
189 | self.angles = angles
190 | self._update_transforms()
191 | self._update_pose()
192 | return self.points_global
193 |
194 | def get_ground_contact_point(self):
195 | # the lowest point as the ground contact
196 | # usual case is the end point of the leg, i.e., tibia
197 | self.ground_contact_point = self.points_global[-1]
198 | for p in self.points_global[::-1]:
199 | if p.z < self.ground_contact_point.z:
200 | self.ground_contact_point = p
201 | return self.ground_contact_point
202 |
203 | def transform(self, transform):
204 | self.global_transform = np.matmul(transform, self.global_transform)
205 | # self.global_transform = transform
206 | for p in self.points_global:
207 | p.set_coordinates(transform.dot(p.get_coordinates_homo()))
208 |
209 | def solve_ik(self, start_p, end_p):
210 | vec_p0_p3 = end_p - start_p
211 | vec_p0_p3_len = np.linalg.norm(vec_p0_p3)
212 | # coxa vector is the projection of the P0->P3 onto the xy-plane
213 | coxa_vec = project_vector_onto_plane(vec_p0_p3, np.array((0, 0, 1)))
214 | coxa_vec_unit = coxa_vec/np.linalg.norm(coxa_vec)
215 | coxa_vec = coxa_vec_unit*self.lengths[0]
216 | p1 = coxa_vec + start_p
217 | vec_p0_p1 = p1 - start_p
218 | alpha = vector_angle(coxa_vec_unit, np.array([0, 1, 0]))
219 | if coxa_vec[0] > 0:
220 | alpha *= -1
221 | rho = vector_angle(coxa_vec, vec_p0_p3, degree=False)
222 | if vec_p0_p3[-1] < 0:
223 | rho*=-1
224 | loc_p3y = vec_p0_p3_len * np.cos(rho)
225 | loc_p3z = vec_p0_p3_len * np.sin(rho)
226 |
227 | vec_p1_p3 = end_p - p1
228 | vec_p1_p3_len = np.linalg.norm(vec_p1_p3)
229 |
230 | if not can_form_triangle(vec_p1_p3_len, self.lengths[1], self.lengths[2]):
231 | # cannot reach the goal, so stretch the segments on the same line
232 | vec_p1_p2 = vec_p1_p3/vec_p1_p3_len*self.lengths[1]
233 | vec_p2_p3 = vec_p1_p3/vec_p1_p3_len*self.lengths[2]
234 | p2 = p1 + vec_p1_p2
235 | p3 = p2 + vec_p2_p3
236 | gamma = 0
237 | beta = vector_angle(vec_p0_p1, vec_p1_p2)
238 | else:
239 | # could form the triangle, use cosine theorem to get the angle between
240 | theta = np.arccos((vec_p1_p3_len**2 + self.lengths[1]**2 - self.lengths[2]**2)/(2*vec_p1_p3_len*self.lengths[1]))
241 | phi = vector_angle(vec_p1_p3, vec_p0_p1, degree=False)
242 | # different cases for the relationship of beta, phi and theta
243 | beta = theta - phi if loc_p3z < 0 else theta + phi
244 | loc_p2z = self.lengths[1]*np.sin(beta)
245 | loc_p2y = vec_p0_p1[1] + self.lengths[1]*np.cos(beta)
246 | vec_p1_p2 = np.array([0, loc_p2y, loc_p2z]) - vec_p0_p1
247 | p2 = p1 + vec_p1_p2
248 | vec_p2_p3 = np.array([0, loc_p3y, loc_p3z]) - np.array([0, loc_p2y, loc_p2z])
249 | p3 = p2 + vec_p2_p3
250 | gamma = vector_angle(vec_p2_p3, vec_p1_p2)
251 | if loc_p2z > loc_p3z:
252 | gamma *= -1
253 | beta = np.rad2deg(beta)
254 |
255 | diff = start_p - np.array(self.points_global[0].get_coordinates())
256 | self.global_transform = np.matmul(get_transformation_homo([0,0,0], diff), self.global_transform)
257 |
258 | # assign to the leg's attributes
259 | self.change_pose([alpha, beta, gamma])
260 |
261 | self.points_global[-1].set_coordinates(end_p)
262 | return alpha, beta, gamma
263 |
264 | def visualize3d(self, fig=None, ax=None):
265 | if fig is None:
266 | fig = plt.figure()
267 | ax = fig.add_subplot(projection="3d", proj_type="persp")
268 | # Points P0-04
269 | for i, p in enumerate(self.points_global):
270 | if i == 0:
271 | color='r'
272 | else:
273 | color='k'
274 | ax.scatter(p.x, p.y, p.z, s=100, color=color)
275 | for l in [(0,1),(1,2),(2,3)]:
276 | px = [self.points_global[l[0]].x, self.points_global[l[1]].x]
277 | py = [self.points_global[l[0]].y, self.points_global[l[1]].y]
278 | pz = [self.points_global[l[0]].z, self.points_global[l[1]].z]
279 | ax.plot(px, py, pz, lw=10, color='royalblue', alpha=0.6)
280 | ax.set_xlabel('x')
281 | ax.set_ylabel('y')
282 | ax.set_zlabel('z')
283 | ax.set_aspect('equal')
284 | return fig, ax
285 |
286 | def visualizeAxis(self, axis='0123', scale=1, fig=None, ax=None):
287 | def plot_axis(ax, global_transform, transform, scale, text='axis'):
288 | px = [scale,0,0,1]
289 | py = [0,scale,0,1]
290 | pz = [0,0,scale,1]
291 | po = [0,0,0,1]
292 | px_t = global_transform.dot(transform.dot(px))
293 | py_t = global_transform.dot(transform.dot(py))
294 | pz_t = global_transform.dot(transform.dot(pz))
295 | po_t = global_transform.dot(transform.dot(po))
296 |
297 | xline, = ax.plot([po_t[0], px_t[0]], [po_t[1], px_t[1]], [po_t[2], px_t[2]], color='red', lw=2)
298 | yline, = ax.plot([po_t[0], py_t[0]], [po_t[1], py_t[1]], [po_t[2], py_t[2]], color='green', lw=2)
299 | zline, = ax.plot([po_t[0], pz_t[0]], [po_t[1], pz_t[1]], [po_t[2], pz_t[2]], color='blue', lw=2)
300 | ax.text(po_t[0], po_t[1], po_t[2], text)
301 | return ax
302 |
303 | if fig is None:
304 | fig = plt.figure()
305 | ax = fig.add_subplot(projection="3d")
306 | for plot_s in axis:
307 | ax = plot_axis(ax, self.global_transform, self.transforms[int(plot_s)], scale, text='P' + plot_s)
308 | ax = plot_axis(ax, np.identity(4), np.identity(4), scale, text='world')
309 | return fig, ax
310 |
311 |
312 | class Hexapod:
313 | def __init__(self, leg_length=DEFAULT_LEG_LENGTH):
314 | self.body = Body(*DEFAULT_DIMSIONS)
315 | self.legs = {}
316 | self.leg_alpha_bias = DEFAULT_LEG_ALPHA_BIAS
317 | self.init_state(DEFAULT_DIMSIONS, leg_length)
318 |
319 | self.walking_sequence = {}
320 | self.generate_walking_sequence(dict(Gait='Tripod', HipSwing=30, LiftSwing=20, StepNum=6,
321 | Direction=1, Rotation=0))
322 |
323 | def init_state(self, body_dim, leg_length):
324 | self.initial_pose = {}
325 | self.body.init_vertices(body_dim)
326 | self.init_legs(leg_length)
327 | self.x_axis = Point3D(1, 0, 0, name='hexapod_x_axis')
328 | self.y_axis = Point3D(0, 1, 0, name='hexapod_y_axis')
329 | self.z_axis = Point3D(0, 0, 1, name='hexapod_z_axis')
330 | self.transform_m = np.identity(4)
331 | self.ground_contact_points = {}
332 | for k, v in self.legs.items():
333 | self.ground_contact_points[k] = v.get_ground_contact_point()
334 | self.ground_contact_points_old = deepcopy(self.ground_contact_points)
335 | self.body_plane_height = 0
336 | return self.update_state()
337 |
338 | def init_legs(self, lengths, init_gamma=DEFAULT_LEG_GAMMA):
339 | for k, v in LEG_ID_NAMES.items():
340 | self.legs[k] = Leg(lengths=lengths, name=v)
341 | self.legs[k].global_transform = get_transformation_homo([0, 0, 0], self.body.vertices[k].get_coordinates())
342 | self.legs[k].angles = [self.leg_alpha_bias[k], 0, init_gamma]
343 | self.initial_pose[v] = {'coxa':self.leg_alpha_bias[k],
344 | 'femur':0,
345 | 'tibia':init_gamma}
346 | self.legs[k]._update_transforms()
347 | self.legs[k]._update_pose()
348 |
349 | def get_legs_pose(self):
350 | pose = {}
351 | for leg_id, leg in self.legs.items():
352 | leg_dict = {}
353 | for k, v in LEG_SEG_NAMES_ID.items():
354 | leg_dict[k] = leg.angles[v]
355 | pose[LEG_ID_NAMES[leg_id]] = leg_dict
356 | return pose
357 |
358 | def update_axis(self, transform=np.identity(4)):
359 | self.x_axis.set_coordinates(transform.dot(self.x_axis.get_coordinates_homo()))
360 | self.y_axis.set_coordinates(transform.dot(self.y_axis.get_coordinates_homo()))
361 | self.z_axis.set_coordinates(transform.dot(self.z_axis.get_coordinates_homo()))
362 |
363 | def transform(self, transform):
364 | self.transform_m = transform.dot(self.transform_m)
365 | self.body.transform(transform)
366 | for l in self.legs.values():
367 | l.transform(transform)
368 | self.update_axis(transform)
369 |
370 | def body_transform(self, transform):
371 | self.transform_m = transform.dot(self.transform_m)
372 | self.body.transform(transform)
373 | self.update_axis(transform)
374 |
375 | def update_leg_pose(self, poses:dict):
376 | '''poses is a dict of dicts in format: {"leg_name":{"leg_seg_name":x degree}}
377 | '''
378 | self.ground_contact_points_old = deepcopy(self.ground_contact_points)
379 | # determine if the hexapod should twist along z-axis due to
380 | # the change of alpha angle of the legs on the ground
381 | body_might_twist = False
382 | cnt = 0
383 | for n in self.ground_contact_points:
384 | if n in poses.keys():
385 | if 'coxa' in poses[n]:
386 | if abs(poses[n]['coxa'] - self.legs[n].angles[0]-self.initial_pose[n][0]) > 0:
387 | cnt += 1
388 | if cnt >= 3:
389 | body_might_twist = True
390 | break
391 |
392 | for leg, v in poses.items():
393 | for leg_seg, angle in v.items():
394 | self.legs[LEG_NAMES_ID[leg]].angles[LEG_SEG_NAMES_ID[leg_seg]] = self.initial_pose[leg][leg_seg] + angle
395 | self.legs[LEG_NAMES_ID[leg]]._update_transforms()
396 | self.legs[LEG_NAMES_ID[leg]]._update_pose()
397 |
398 | return self.update_state(body_might_twist)
399 |
400 | def update_leg_pattern(self, angles):
401 | self.ground_contact_points_old = deepcopy(self.ground_contact_points)
402 | cnt = 0
403 | # all the legs share the same pose
404 | for i, l in enumerate(self.legs.values()):
405 | if abs(angles[0] - DEFAULT_LEG_ALPHA_BIAS[i] - l.angles[0]) > 0:
406 | cnt += 1
407 | l.angles = [angles[0] + DEFAULT_LEG_ALPHA_BIAS[i], angles[1], angles[2] + DEFAULT_LEG_GAMMA]
408 | l._update_transforms()
409 | l._update_pose()
410 |
411 | return self.update_state(body_might_twist=(cnt>=3))
412 |
413 | def update_dimensions(self, dimension):
414 | '''dimension is a list: [f, m, s, coxa, femur, tibia]
415 | '''
416 | return self.init_state(dimension[:3], dimension[3:])
417 |
418 | def update_state(self, body_might_twist=False):
419 | '''update the pose of the robot
420 | '''
421 | is_stable = False
422 | # find the ground contact point constructing the support polygon
423 | for leg_inds in LEG_TRIOS:
424 | p0, p1, p2 = [self.legs[i].get_ground_contact_point() for i in leg_inds]
425 |
426 | # justify if the cog is in the triangle formed by these legs
427 | if not is_projected_point_within_triangle(np.array(self.body.cog.get_coordinates()),
428 | [np.array(p0.get_coordinates()),
429 | np.array(p1.get_coordinates()),
430 | np.array(p2.get_coordinates())]):
431 | continue
432 | n = get_plane_norm(np.array(p0.get_coordinates()),
433 | np.array(p1.get_coordinates()),
434 | np.array(p2.get_coordinates()))
435 | # get distance from the cog to the support polygon plane
436 | d = n.dot((self.body.cog - p0).get_coordinates())
437 |
438 | # check if this trio constructs the lowest plane (i.e., the biggest d)
439 | others = [self.legs[i].get_ground_contact_point() for i in set(LEG_ID_NAMES.keys()) - set(leg_inds)]
440 | r = True
441 | for p in others:
442 | d_ = n.dot((self.body.cog - p).get_coordinates())
443 | if d_ > d:
444 | r = False
445 | if r:
446 | is_stable = True
447 | self.body_plane_norm = n
448 | break
449 |
450 | if is_stable:
451 | self.ground_contact_points = {}
452 | for leg_id in leg_inds:
453 | self.ground_contact_points[leg_id] = self.legs[leg_id].get_ground_contact_point()
454 | # get all the legs' end tip that contacts the ground
455 | for leg_id in set(LEG_ID_NAMES.keys()) - set(leg_inds):
456 | for p in reversed(self.legs[leg_id].points_global[1:]):
457 | d_ = n.dot((self.body.cog - p).get_coordinates())
458 | if np.isclose(d, d_):
459 | self.ground_contact_points[leg_id] = p
460 | break
461 | # tilt the hexapod according to the new plane norm
462 | rot_m = get_rotation_matrix_align_vectors(self.body_plane_norm, np.array([0, 0, 1]))
463 | t = combine_rot_trans_to_homo(rot_m, [0, 0, d - self.body_plane_height])
464 | self.transform(t)
465 | self.body_plane_height = d
466 | # twist body if needed
467 | if body_might_twist:
468 | # find one pair of point to get the twist angle
469 | for k, v in self.ground_contact_points_old.items():
470 | if k in self.ground_contact_points:
471 | a = np.arctan2(v.y, v.x)-np.arctan2(self.ground_contact_points[k].y, self.ground_contact_points[k].x)
472 | t = get_transformation_homo([0,0,np.rad2deg(a)],[0,0,0])
473 | self.transform(t)
474 | break
475 | return True
476 | else:
477 | print('The pose is not stable, keep previous pose')
478 | return False
479 |
480 | def solve_ik(self, rot, trans):
481 | # reset hexapod
482 | self.init_state((self.body.f, self.body.m, self.body.s), self.legs[0].lengths)
483 | # restore old body contacts
484 | old_body_contacts = deepcopy(self.body.vertices)
485 | # transform body to get new body contacts
486 | self.body_transform(get_transformation_homo(rot, trans))
487 | # solve IK for each leg
488 | for k, leg in self.legs.items():
489 | leg.solve_ik(np.array(self.body.vertices[k].get_coordinates()),
490 | np.array(self.ground_contact_points[k].get_coordinates()))
491 |
492 | def generate_walking_sequence(self, parameters:dict):
493 | gait = parameters['Gait']
494 | d_alpha = parameters['HipSwing']
495 | d_beta = parameters['LiftSwing']
496 | d_gamma = -parameters['LiftSwing']/2
497 | step_num = parameters['StepNum']
498 | move_dir = parameters['Direction']
499 | rotation = parameters['Rotation']
500 | self.init_state((self.body.f, self.body.m, self.body.s), self.legs[0].lengths)
501 | self.walking_sequence = {}
502 | if gait == 'Tripod':
503 | for k, leg in self.legs.items():
504 | beta_s = np.linspace(0, d_beta, int(step_num))
505 | beta_s_r = beta_s[::-1]
506 | beta_s_0 = np.ones(int(len(beta_s)*2))*beta_s[0]
507 | gamma_s = np.linspace(0, d_gamma, int(step_num))
508 | gamma_s_r = gamma_s[::-1]
509 | gamma_s_0 = np.ones(int(len(gamma_s)*2))*gamma_s[0]
510 | if rotation != 0:
511 | alpha_s = np.linspace(-d_alpha, d_alpha, int(step_num*2))
512 | alpha_s_r = alpha_s[::-1]
513 | else:
514 | if k in (2, 3, 4):
515 | alpha_s = np.linspace(d_alpha, -d_alpha, int(step_num*2))
516 | alpha_s_r = alpha_s[::-1]
517 | else:
518 | alpha_s = np.linspace(-d_alpha, d_alpha, int(step_num*2))
519 | alpha_s_r = alpha_s[::-1]
520 | alpha_seq_a = np.hstack([alpha_s, alpha_s_r])
521 | alpha_seq_b = np.hstack([alpha_s_r, alpha_s])
522 | if k in (0, 2, 4):
523 | self.walking_sequence[k] = {'coxa':alpha_seq_a,
524 | 'femur':np.hstack([beta_s, beta_s_r, beta_s_0]),
525 | 'tibia':np.hstack([gamma_s, gamma_s_r, gamma_s_0])}
526 | else:
527 | self.walking_sequence[k] = {'coxa':alpha_seq_b,
528 | 'femur':np.hstack([beta_s_0, beta_s, beta_s_r]),
529 | 'tibia':np.hstack([gamma_s_0, gamma_s, gamma_s_r])}
530 | elif gait == 'Ripple':
531 | pass
532 |
533 | def set_pose_from_walking_sequence(self, step):
534 | poses = {}
535 | for k, v in self.walking_sequence.items():
536 | P = {}
537 | for seg in LEG_SEG_NAMES_ID.keys():
538 | P[seg] = v[seg][step]
539 | poses[LEG_ID_NAMES[k]] = P
540 | return self.update_leg_pose(poses)
541 |
542 |
543 | def visualize3d(self, fig=None, ax=None):
544 | if fig is None:
545 | fig = plt.figure()
546 | ax = fig.add_subplot(projection="3d")
547 | fig, ax = self.body.visualize3d(fig, ax)
548 | for k, leg in self.legs.items():
549 | fig, ax = leg.visualize3d(fig, ax)
550 | # hexapod axis
551 | ax.plot([self.body.cog.x, self.x_axis.x],
552 | [self.body.cog.y, self.x_axis.y],
553 | [self.body.cog.z, self.x_axis.z],
554 | color='red')
555 | ax.plot([self.body.cog.x, self.y_axis.x],
556 | [self.body.cog.y, self.y_axis.y],
557 | [self.body.cog.z, self.y_axis.z],
558 | color='green')
559 | ax.plot([self.body.cog.x, self.z_axis.x],
560 | [self.body.cog.y, self.z_axis.y],
561 | [self.body.cog.z, self.z_axis.z],
562 | color='blue')
563 | ax.set_aspect('equal')
564 | ax.set_zlim([0,6])
565 | return fig, ax
566 |
567 |
568 | if __name__ == "__main__":
569 | # hexapod = Hexapod()
570 | # fig1, ax1 = hexapod.visualize3d()
571 | # hexapod.solve_ik([0, 6, 2], [0, 0, 0.2])
572 | # print(hexapod.get_legs_pose())
573 | # fig2, ax2 = hexapod.visualize3d()
574 | # plt.show()
575 |
576 | # leg = Leg(lengths=[2,2,3])
577 | # t = get_transformation_homo([0, 0, 45], [0,4,0])
578 | # leg.change_pose([-60, 45, 30])
579 | # leg.transform(t)
580 | # fig, ax = leg.visualize3d()
581 | # fig, ax = leg.visualizeAxis(fig=fig, ax=ax, scale=1)
582 | # plt.show()
583 | pass
--------------------------------------------------------------------------------
/style.ini:
--------------------------------------------------------------------------------
1 | [robot plotter]
2 | body_color: #9BC2F4
3 | body_outline_width: 8
4 | leg_color: #82B4F4
5 | leg_width: 10
6 | joint_size: 8
7 | head_color: red
8 | head_size: 10
9 | cog_color: gray
10 | cog_width: 6
11 | [axis]
12 | color_x: red
13 | color_y: green
14 | color_z: blue
15 | w_origin_color: black
16 | r_origin_color: orange
17 | origin_size: 6
18 | axis_size: 2
19 | [ground]
20 | size: 60
21 | color: gray
22 |
--------------------------------------------------------------------------------
/ui.py:
--------------------------------------------------------------------------------
1 | import configparser
2 |
3 | import dash
4 | from dash import html, dcc
5 | import dash_bootstrap_components as dbc
6 | from dash import html, dcc, Input, Output, callback, State
7 | import plotly.graph_objects as go
8 |
9 | from constant import *
10 | from models import Hexapod
11 |
12 | # dimension control
13 | def make_slider(range, id, value, step=1, updatemode='drag'):
14 | return dcc.Slider(range[0], range[1], step,
15 | value=value,
16 | id=id, marks=None,
17 | updatemode = updatemode,
18 | tooltip={"placement": "right", "always_visible": True})
19 |
20 | dim_ctl_ids = ['Front', 'Middle', 'Side', 'coxa', 'Femur', 'Tibia']
21 | dim_ctl_labels = [html.Label(id) for id in dim_ctl_ids]
22 | values = DEFAULT_DIMSIONS + DEFAULT_LEG_LENGTH
23 | dim_ctl_sliders = [make_slider([1, 20], id, v) for id, v in zip(dim_ctl_ids, values)]
24 | dim_ctl_widgets = [dbc.Row(dbc.Col(html.Label(dcc.Markdown(f"**Dimension Setting**")), width=12), justify='center')]
25 | for l, s in zip(dim_ctl_labels, dim_ctl_sliders):
26 | dim_ctl_widgets.append(dbc.Row([dbc.Col(l, width=2, align='start'),
27 | dbc.Col(s, width=10, align='start', className="g-0")],
28 | justify='center'))
29 | dim_ctl_widgets.append(dbc.Row(dbc.Col(dbc.Button("Reset Dimension", outline=True, color="primary", className="me-1", id='reset-dim'), width=12), align='center',className="mt-3",))
30 | dim_ctl_widgets.append(dbc.Row(dbc.Col(dbc.Button("Reset Poses", outline=True, color="primary", className="me-1", id='reset-pose'), width=12), align='center',className="mt-3"))
31 | dim_ctl_widgets.append(dbc.Row(dbc.Col(dbc.Button("Reset 3D View", outline=True, color="primary", className="me-1", id='reset-view'), width=12), align='center',className="mt-3"))
32 |
33 | # leg patterns
34 | leg_ctl_ids = ['alpha', 'beta', 'gamma']
35 | leg_labels = [r'$\alpha$ (coxa-zaxis)', r'$\beta$ (femur-xaxis)', r'$\gamma$ (tibia-xaxis)']
36 | leg_ctl_labels = [html.Div(dcc.Markdown(id, mathjax=True)) for id in leg_labels]
37 | leg_ctl_sliders = [make_slider([-180, 180], id, 0) for id in leg_ctl_ids]
38 | widgets = [html.Label(dcc.Markdown("*Legs share the same pose*"))]
39 | for l, s in zip(leg_ctl_labels, leg_ctl_sliders):
40 | widgets.append(l)
41 | widgets.append(s)
42 |
43 | leg_ctl_widgets = dbc.Card(
44 | dbc.CardBody(
45 | widgets
46 | ),
47 | className="mt-3",
48 | )
49 |
50 | # forward kinematics
51 | fk_leg_labels = []
52 | for v in LEG_ID_NAMES.values():
53 | fk_leg_labels.append(dbc.Col(html.Label(dcc.Markdown(f"{v}")), width=2, align='center'))
54 |
55 | fk_sliders = []
56 | fk_leg_ctl_ids = ['-fk-alpha', '-fk-beta', '-fk-gamma']
57 | fk_leg_seg_labels = [r'$\alpha$', r'$\beta$', r'$\gamma$']
58 | fk_slider_ids = []
59 | for id, l in zip(fk_leg_ctl_ids, fk_leg_seg_labels):
60 | l_s = []
61 | for v in LEG_ID_NAMES.values():
62 | # l_s.append(dbc.Col(html.Div(dcc.Markdown(l, mathjax=True)), width=1))
63 | s = make_slider([-180, 180], v + id, 0)
64 | fk_slider_ids.append(v + id)
65 | l_s.append(dbc.Col([html.Label(dcc.Markdown(l, mathjax=True)), s], width=2, align='center'))
66 | fk_sliders.append(dbc.Row(l_s))
67 |
68 | fk_widgets = [dbc.Row(fk_leg_labels, align='center')] + fk_sliders
69 | fk_ctl_widgets = dbc.Card(
70 | dbc.CardBody(
71 | fk_widgets
72 | ),
73 | className="mt-3",
74 | )
75 |
76 | # inverse kinematics
77 | ik_t_slider = []
78 | ik_r_slider = []
79 | for axis in AXIS_INDEX.keys():
80 | ts = make_slider([-1, 1], 'IK-T'+axis, 0, step=0.01)
81 | ik_t_slider.append(dbc.Col([html.Label(dcc.Markdown('T'+axis, mathjax=True)), ts], width=4))
82 | rs = make_slider([-30, 30], 'IK-R'+axis, 0, step=0.1)
83 | ik_r_slider.append(dbc.Col([html.Label(dcc.Markdown('R'+axis, mathjax=True)), rs], width=4))
84 |
85 | ik_stance_slider = [
86 | dbc.Col([html.Label(dcc.Markdown('Hip Stance', mathjax=True)), make_slider([-60, 60], 'IK-Hip Stance', 0, step=1)], width=6),
87 | dbc.Col([html.Label(dcc.Markdown('Leg Stance', mathjax=True)), make_slider([-60, 60], 'IK-Leg Stance', 0, step=1)], width=6)
88 | ]
89 |
90 | ik_ctl_widgets = dbc.Card(
91 | dbc.CardBody(
92 | [dbc.Row(ik_t_slider), dbc.Row(ik_r_slider), dbc.Row(ik_stance_slider)]
93 | ),
94 | className="mt-3",
95 | )
96 |
97 | # walking gait
98 | gait_timer = dcc.Interval(id='walking-timer',
99 | interval=20, # in milliseconds
100 | n_intervals=0,
101 | max_intervals=0
102 | )
103 | gait_play_bt = dbc.Button("Play", outline=True, color="primary", className="me-1", id='gait-play')
104 | gait_pause_bt = dbc.Button("Pause", outline=True, color="primary", className="me-1", id='gait-pause')
105 | gait_step_bt = dbc.Button(">>Step", outline=True, color="primary", className="me-1", id='gait-step')
106 |
107 | gait_ck = dcc.Checklist(
108 | [ {
109 | "label": html.Div(['Tripod'], style={'color': 'LightGreen', 'font-size': 20}),
110 | "value": 'is_tripod',
111 | },
112 | {
113 | "label": html.Div(['Forward'], style={'color': 'Gold', 'font-size': 20}),
114 | "value": 'is_forward',
115 | },
116 | {
117 | "label": html.Div(['Rotate'], style={'color': 'MediumTurqoise', 'font-size': 20}),
118 | "value": 'is_rotate',
119 | },
120 | ],
121 | value=['is_tripod', 'is_forward'],
122 | labelStyle={"display": "flex", "align-items": "center"},
123 | id='gait-ck'
124 | )
125 |
126 | lift_swing_slider = make_slider([10,40], id='LiftSwing', value=20, step=1, updatemode='mouseup')
127 | hip_swing_slider = make_slider([10,40], id='HipSwing', value=12, step=1, updatemode='mouseup')
128 | step_swing_slider = make_slider([5,20], id='GaitStep', value=10, step=1, updatemode='mouseup')
129 | gait_speed_slider = make_slider([5,20], id='GaitSpeed', value=10, step=1, updatemode='mouseup')
130 | gait_sliders = [lift_swing_slider, hip_swing_slider, step_swing_slider, gait_speed_slider]
131 | gait_slider_label = []
132 | for s in gait_sliders:
133 | gait_slider_label.append(html.Label(s.id))
134 | gait_widget = dbc.Card(
135 | dbc.CardBody(
136 | dbc.Row([
137 | dbc.Col(gait_slider_label, width=1),
138 | dbc.Col(gait_sliders, width=4),
139 | dbc.Col(gait_ck, width=3),
140 | dbc.Col([gait_play_bt, gait_pause_bt, gait_step_bt], width=3),
141 | gait_timer
142 | ])
143 | ),
144 | className="mt-3",
145 | )
146 |
147 | # configures
148 | conf = configparser.ConfigParser()
149 | conf.read('style.ini', encoding='utf-8')
150 |
151 | def draw_robot(robot:Hexapod):
152 | # generate data for hexapod plotting
153 | body_mesh = go.Mesh3d(
154 | x=[p.x for p in robot.body.vertices],
155 | y=[p.y for p in robot.body.vertices],
156 | z=[p.z for p in robot.body.vertices],
157 | color=conf["robot plotter"]['body_color'],
158 | name='robot-body-mesh',
159 | showlegend=False,
160 | opacity=0.7,
161 | i=[0,1,0,0],
162 | j=[1,2,3,4],
163 | k=[3,3,4,5],
164 | )
165 |
166 | body_outline = go.Scatter3d(
167 | x=[p.x for p in robot.body.vertices] + [robot.body.vertices[0].x],
168 | y=[p.y for p in robot.body.vertices] + [robot.body.vertices[0].y],
169 | z=[p.z for p in robot.body.vertices] + [robot.body.vertices[0].z],
170 | name='robot-body_outline',
171 | marker=dict(color=conf["robot plotter"]['leg_color'],
172 | size=int(conf["robot plotter"]['joint_size'])),
173 | line=dict(width=int(conf["robot plotter"]['body_outline_width'])),
174 | showlegend=False
175 | )
176 |
177 | head = go.Scatter3d(
178 | x=[robot.body.head.x],
179 | y=[robot.body.head.y],
180 | z=[robot.body.head.z],
181 | name='robot-head',
182 | marker=dict(color=conf["robot plotter"]['head_color'],
183 | size=int(conf["robot plotter"]['head_size'])),
184 | )
185 |
186 |
187 | graph_data = [body_mesh, body_outline, head]
188 |
189 | for i in range(6):
190 | leg = go.Scatter3d(
191 | x=[p.x for p in robot.legs[i].points_global],
192 | y=[p.y for p in robot.legs[i].points_global],
193 | z=[p.z for p in robot.legs[i].points_global],
194 | name='robot-leg-' + str(i),
195 | marker=dict(color=conf["robot plotter"]['leg_color'],
196 | size=int(conf["robot plotter"]['joint_size'])),
197 | line=dict(width=int(conf["robot plotter"]['leg_width'])),
198 | showlegend=False
199 | )
200 | graph_data.append(leg)
201 |
202 | support_mesh = go.Mesh3d(
203 | x=[p.x for p in robot.ground_contact_points.values()],
204 | y=[p.y for p in robot.ground_contact_points.values()],
205 | z=[p.z-0.01 for p in robot.ground_contact_points.values()],
206 | color=conf["robot plotter"]['body_color'],
207 | name='support-mesh',
208 | showlegend=False,
209 | opacity=0.2,
210 | )
211 | graph_data.append(support_mesh)
212 |
213 | robot_axis = [
214 | go.Scatter3d(
215 | x=[robot.body.cog.x],
216 | y=[robot.body.cog.y],
217 | z=[robot.body.cog.z],
218 | name='robot-axis',
219 | marker=dict(color=conf["axis"]['r_origin_color'],
220 | size=int(conf["axis"]['origin_size']))
221 | ),
222 | # x-axis
223 | go.Scatter3d(
224 | x = [robot.body.cog.x, robot.x_axis.x],
225 | y = [robot.body.cog.y, robot.x_axis.y],
226 | z = [robot.body.cog.z, robot.x_axis.z],
227 | mode='lines',
228 | line=dict(color=conf["axis"]['color_x']),
229 | showlegend=False
230 | ),
231 | go.Scatter3d(
232 | x = [robot.body.cog.x, robot.y_axis.x],
233 | y = [robot.body.cog.y, robot.y_axis.y],
234 | z = [robot.body.cog.z, robot.y_axis.z],
235 | mode='lines',
236 | line=dict(color=conf["axis"]['color_y']),
237 | showlegend=False
238 | ),
239 | go.Scatter3d(
240 | x = [robot.body.cog.x, robot.z_axis.x],
241 | y = [robot.body.cog.y, robot.z_axis.y],
242 | z = [robot.body.cog.z, robot.z_axis.z],
243 | mode='lines',
244 | line=dict(color=conf["axis"]['color_z']),
245 | showlegend=False
246 | )
247 | ]
248 |
249 | world_axis = [
250 | go.Scatter3d(
251 | x=[0],
252 | y=[0],
253 | z=[0],
254 | name='world-axis',
255 | marker=dict(color=conf["axis"]['w_origin_color'],
256 | size=int(conf["axis"]['origin_size']))
257 | ),
258 | # x-axis
259 | go.Scatter3d(
260 | x = [0, conf["axis"]['axis_size']],
261 | y = [0, 0],
262 | z = [0, 0],
263 | mode='lines',
264 | line=dict(color=conf["axis"]['color_x']),
265 | showlegend=False
266 | ),
267 | # y-axis
268 | go.Scatter3d(
269 | x = [0, 0],
270 | y = [0, conf["axis"]['axis_size']],
271 | z = [0, 0],
272 | mode='lines',
273 | line=dict(color=conf["axis"]['color_y']),
274 | showlegend=False
275 | ),
276 | # z-axis
277 | go.Scatter3d(
278 | x = [0, 0],
279 | y = [0, 0],
280 | z = [0, conf["axis"]['axis_size']],
281 | mode='lines',
282 | line=dict(color=conf["axis"]['color_z']),
283 | showlegend=False
284 | )
285 | ]
286 | graph_data += robot_axis + world_axis
287 |
288 | # ground
289 | s = int(conf['ground']['size'])
290 | ground_mesh = go.Mesh3d(
291 | x=[s/2, -s/2, -s/2, s/2],
292 | y=[s/2, s/2, -s/2, -s/2],
293 | z=[0, 0, 0, 0],
294 | color=conf['ground']['color'],
295 | name='ground',
296 | showlegend=False,
297 | opacity=0.2,
298 | showscale=False
299 |
300 | )
301 |
302 | graph_data += [ground_mesh]
303 | return graph_data
304 |
305 |
306 | def update_robot_graph(fig, robot:Hexapod):
307 | # body mesh
308 | fig["data"][0]['x'] = [p.x for p in robot.body.vertices]
309 | fig["data"][0]['y'] = [p.y for p in robot.body.vertices]
310 | fig["data"][0]['z'] = [p.z for p in robot.body.vertices]
311 |
312 | # body outline
313 | fig["data"][1]['x'] = [p.x for p in robot.body.vertices] + [robot.body.vertices[0].x]
314 | fig["data"][1]['y'] = [p.y for p in robot.body.vertices] + [robot.body.vertices[0].y]
315 | fig["data"][1]['z'] = [p.z for p in robot.body.vertices] + [robot.body.vertices[0].z]
316 |
317 | # head
318 | fig["data"][2]['x'] = [robot.body.head.x]
319 | fig["data"][2]['y'] = [robot.body.head.y]
320 | fig["data"][2]['z'] = [robot.body.head.z]
321 |
322 | # robot legs
323 | for i in range(6):
324 | fig["data"][i+3]['x'] = [p.x for p in robot.legs[i].points_global]
325 | fig["data"][i+3]['y'] = [p.y for p in robot.legs[i].points_global]
326 | fig["data"][i+3]['z'] = [p.z for p in robot.legs[i].points_global]
327 |
328 | # support mesh
329 | fig["data"][9]['x'] = [p.x for p in robot.ground_contact_points.values()]
330 | fig["data"][9]['y'] = [p.y for p in robot.ground_contact_points.values()]
331 | fig["data"][9]['z'] = [p.z-0.01 for p in robot.ground_contact_points.values()]
332 |
333 | # robot axis
334 | fig["data"][10]['x'] = [robot.body.cog.x]
335 | fig["data"][10]['y'] = [robot.body.cog.y]
336 | fig["data"][10]['z'] = [robot.body.cog.z]
337 |
338 | fig["data"][11]['x'] = [robot.body.cog.x, robot.x_axis.x]
339 | fig["data"][11]['y'] = [robot.body.cog.y, robot.x_axis.y]
340 | fig["data"][11]['z'] = [robot.body.cog.z, robot.x_axis.z]
341 |
342 | fig["data"][12]['x'] = [robot.body.cog.x, robot.y_axis.x]
343 | fig["data"][12]['y'] = [robot.body.cog.y, robot.y_axis.y]
344 | fig["data"][12]['z'] = [robot.body.cog.z, robot.y_axis.z]
345 |
346 | fig["data"][13]['x'] = [robot.body.cog.x, robot.z_axis.x]
347 | fig["data"][13]['y'] = [robot.body.cog.y, robot.z_axis.y]
348 | fig["data"][13]['z'] = [robot.body.cog.z, robot.z_axis.z]
349 |
350 | return fig
351 |
352 | def play_robot_walking(fig, robot:Hexapod, t):
353 | robot.set_pose_from_walking_sequence(t)
354 | return update_robot_graph(fig, robot)
355 |
356 |
357 | # robot instance
358 | robot = Hexapod()
359 | graph_data = draw_robot(robot)
360 |
361 | camera = dict(
362 | up=dict(x=0, y=0, z=1),
363 | center=dict(x=0, y=0, z=0),
364 | eye=dict(x=0, y=0.5, z=0.4)
365 | )
366 |
367 | fig = go.Figure(data=graph_data)
368 | fig.update_layout(height=600,
369 | uirevision=True,
370 | scene={
371 | "camera":camera,
372 | "aspectmode": "manual",
373 | "aspectratio": {"x": 1, "y": 1, "z": 1},
374 | 'xaxis':{"nticks":1, "backgroundcolor":"white", "range": [-20, 20], "tickfont":dict(color="white")},
375 | 'yaxis':{"nticks":1, "backgroundcolor":"white", "range": [-20, 20], "tickfont":dict(color="white")},
376 | 'zaxis':{"nticks":1, "backgroundcolor":"white", "range": [-20, 20], "tickfont":dict(color="white")},
377 | })
378 | # buttons
379 | @callback(
380 | Output('Front', 'value'),
381 | Output('Middle', 'value'),
382 | Output('Side', 'value'),
383 | Output('coxa', 'value'),
384 | Output('Femur', 'value'),
385 | Output('Tibia', 'value'),
386 | Input('reset-dim', 'n_clicks'),
387 | prevent_initial_call=True
388 | )
389 | def reset_robot_dimension(btn):
390 | return DEFAULT_DIMSIONS + DEFAULT_LEG_LENGTH
391 |
392 |
393 | @callback(
394 | Output('graph', 'figure', allow_duplicate=True),
395 | Input('reset-view', 'n_clicks'),
396 | prevent_initial_call=True
397 | )
398 | def reset_camera_view(btn):
399 | fig['layout']['uirevision'] = False
400 | fig['layout']['scene']['camera'] = camera
401 | # fig['layout']['uirevision'] = True
402 | return fig
403 |
404 |
405 | # robot control
406 | # dimension
407 | @callback(
408 | Output('graph', 'figure', allow_duplicate=True),
409 | Input('Front', 'value'),
410 | Input('Middle', 'value'),
411 | Input('Side', 'value'),
412 | Input('coxa', 'value'),
413 | Input('Femur', 'value'),
414 | Input('Tibia', 'value'),
415 | prevent_initial_call=True
416 | )
417 | def change_robot_dimension(f, m, s, coxa, femur, tibia):
418 | if robot.update_dimensions([f, m, s, coxa, femur, tibia]):
419 | update_robot_graph(fig, robot)
420 | return fig
421 | # leg patterns
422 | @callback(
423 | Output('graph', 'figure'),
424 | Input('alpha', 'value'),
425 | Input('beta', 'value'),
426 | Input('gamma', 'value'),
427 | prevent_initial_call=True
428 | )
429 | def change_robot_leg_pattern(a,b,c):
430 | if robot.update_leg_pattern([a, b, c]):
431 | update_robot_graph(fig, robot)
432 | return fig
433 |
434 | # forward kinematics
435 | html_e = [Output('graph', 'figure', allow_duplicate=True)]
436 | for eid in fk_slider_ids:
437 | html_e.append(Input(eid, "value"))
438 | @callback(
439 | *html_e, prevent_initial_call=True
440 | )
441 | def forward_kinematics(*args):
442 | poses = {}
443 | for leg, leg_id in LEG_NAMES_ID.items():
444 | a = {}
445 | for seg, seg_id in LEG_SEG_NAMES_ID.items():
446 | a[seg] = args[int(leg_id + seg_id*6)]
447 | poses[leg] = a
448 | if robot.update_leg_pose(poses):
449 | update_robot_graph(fig, robot)
450 | return fig
451 |
452 | # inverse kinematics
453 | @callback(
454 | Output('graph', 'figure', allow_duplicate=True),
455 | Input('IK-RX', 'value'),
456 | Input('IK-RY', 'value'),
457 | Input('IK-RZ', 'value'),
458 | Input('IK-TX', 'value'),
459 | Input('IK-TY', 'value'),
460 | Input('IK-TZ', 'value'),
461 | prevent_initial_call=True
462 | )
463 | def inverse_kinematics(rx, ry, rz, tx, ty, tz):
464 | tx *= robot.body.f
465 | ty *= robot.body.s
466 | tz *= robot.legs[0].lengths[-1]
467 | robot.solve_ik([rx, ry, rz], [tx, ty, tz])
468 | update_robot_graph(fig, robot)
469 | return fig
470 |
471 | # gait
472 | @callback(
473 | Output('graph', 'figure', allow_duplicate=True),
474 | Input('walking-timer', 'n_intervals'),
475 | prevent_initial_call=True
476 | )
477 | def walking(n):
478 | play_robot_walking(fig, robot, n%len(robot.walking_sequence[0]['coxa']))
479 | return fig
480 |
481 | @callback(
482 | Output('walking-timer', 'max_intervals', allow_duplicate=True),
483 | Input('gait-play', 'n_clicks'),
484 | prevent_initial_call=True
485 | )
486 | def play_gait(n):
487 | return -1
488 |
489 | @callback(
490 | Output('walking-timer', 'max_intervals'),
491 | Input('gait-pause', 'n_clicks'),
492 | prevent_initial_call=True
493 | )
494 | def pause_gait(n):
495 | return 0
496 |
497 | @callback(
498 | Output('walking-timer', 'n_intervals'),
499 | Input('gait-step', 'n_clicks'),
500 | State('walking-timer', 'n_intervals'),
501 | prevent_initial_call=True
502 | )
503 | def pause_gait(s, n):
504 | return s + 1
505 |
506 | @callback(
507 | Output('walking-timer', 'n_intervals', allow_duplicate=True),
508 | Input('LiftSwing', 'value'),
509 | Input('HipSwing', 'value'),
510 | Input('GaitStep', 'value'),
511 | Input('GaitSpeed', 'value'),
512 | Input('gait-ck', 'value'),
513 | prevent_initial_call=True
514 | )
515 | def update_gait_parameters(ls, hs, st, sp, ck):
516 | para = {}
517 | para['HipSwing'] = hs
518 | para['LiftSwing'] = ls
519 | para['StepNum'] = st
520 | para['Speed'] = sp
521 | para['Gait'] = 'Tripod' if 'is_tripod' in ck else 'Ripple'
522 | para['Direction'] = 1 if 'is_forward' in ck else -1
523 | para['Rotation'] = 1 if 'is_rotate' in ck else 0
524 | robot.generate_walking_sequence(para)
525 | print(para)
526 | return 0
527 |
528 | if __name__ == "__main__":
529 | app = dash.Dash(
530 | external_stylesheets=[dbc.themes.BOOTSTRAP]
531 | )
532 |
533 | app.layout = html.Div(
534 | dbc.Container(
535 | [
536 | dbc.Row([
537 | dbc.Col(dim_ctl_widgets, width={"size": 3, "offset": 0}, align='center'),
538 | dbc.Col(
539 | html.Div(dcc.Graph(figure=fig, id='graph')),
540 | width={"size": 9, "offset": 0},
541 | )
542 | ], align='center', justify='center'),
543 |
544 | dbc.Row([
545 | dcc.Tabs(id="page-tabs", value='leg-patterns',
546 | children=[
547 | dcc.Tab(children=leg_ctl_widgets, label='Leg Pattern', value='leg-patterns'),
548 | dcc.Tab(children=fk_ctl_widgets,label='Forward Kinematics', value='FK'),
549 | dcc.Tab(children=ik_ctl_widgets,label='Inverse Kinematics', value='IK'),
550 | dcc.Tab(children=gait_widget, label='Walking Gaits', value='Walk'),
551 | ])
552 | ]),
553 | ]
554 | )
555 | )
556 |
557 | app.run_server(debug=True)
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