|
5 | 5 | import math |
6 | 6 |
|
7 | 7 |
|
8 | | -def p_servo(wTe, wTep, gain=2, threshold=0.1): |
9 | | - """ |
10 | | - Position-based servoing. |
11 | | -
|
12 | | - Returns the end-effector velocity which will cause the robot to approach |
13 | | - the desired pose. |
14 | | -
|
15 | | - :param wTe: The current pose of the end-effecor in the base frame. |
16 | | - :type wTe: SE3 |
17 | | - :param wTep: The desired pose of the end-effecor in the base frame. |
18 | | - :type wTep: SE3 |
19 | | - :param gain: The gain for the controller |
20 | | - :type gain: float |
21 | | - :param threshold: The threshold or tolerance of the final error between |
22 | | - the robot's pose and desired pose |
23 | | - :type threshold: float |
24 | | -
|
25 | | - :returns v: The velocity of the end-effecotr which will casue the robot |
26 | | - to approach wTep |
27 | | - :rtype v: ndarray(6) |
28 | | - :returns arrived: True if the robot is within the threshold of the final |
29 | | - pose |
30 | | - :rtype arrived: bool |
31 | | -
|
32 | | - """ |
| 8 | +# def p_servo(wTe, wTep, gain=2, threshold=0.1): |
| 9 | +# """ |
| 10 | +# Position-based servoing. |
33 | 11 |
|
34 | | - if not isinstance(wTe, SE3): |
35 | | - wTe = SE3(wTe) |
| 12 | +# Returns the end-effector velocity which will cause the robot to approach |
| 13 | +# the desired pose. |
36 | 14 |
|
37 | | - if not isinstance(wTep, SE3): |
38 | | - wTep = SE3(wTep) |
| 15 | +# :param wTe: The current pose of the end-effecor in the base frame. |
| 16 | +# :type wTe: SE3 |
| 17 | +# :param wTep: The desired pose of the end-effecor in the base frame. |
| 18 | +# :type wTep: SE3 |
| 19 | +# :param gain: The gain for the controller |
| 20 | +# :type gain: float |
| 21 | +# :param threshold: The threshold or tolerance of the final error between |
| 22 | +# the robot's pose and desired pose |
| 23 | +# :type threshold: float |
39 | 24 |
|
40 | | - # Pose difference |
41 | | - eTep = wTe.inv() * wTep |
| 25 | +# :returns v: The velocity of the end-effecotr which will casue the robot |
| 26 | +# to approach wTep |
| 27 | +# :rtype v: ndarray(6) |
| 28 | +# :returns arrived: True if the robot is within the threshold of the final |
| 29 | +# pose |
| 30 | +# :rtype arrived: bool |
42 | 31 |
|
43 | | - # Translational error |
44 | | - ev = eTep.t |
| 32 | +# """ |
45 | 33 |
|
46 | | - # Angular error |
47 | | - ew = eTep.rpy("rad") |
| 34 | +# if not isinstance(wTe, SE3): |
| 35 | +# wTe = SE3(wTe) |
48 | 36 |
|
49 | | - # Form error vector |
50 | | - e = np.r_[ev, ew] |
| 37 | +# if not isinstance(wTep, SE3): |
| 38 | +# wTep = SE3(wTep) |
51 | 39 |
|
52 | | - # Desired end-effector velocity |
53 | | - v = gain * e |
| 40 | +# # Pose difference |
| 41 | +# eTep = wTe.inv() * wTep |
54 | 42 |
|
55 | | - if np.sum(np.abs(e)) < threshold: |
56 | | - arrived = True |
57 | | - else: |
58 | | - arrived = False |
| 43 | +# # Translational error |
| 44 | +# ev = eTep.t |
59 | 45 |
|
60 | | - return v, arrived |
| 46 | +# # Angular error |
| 47 | +# ew = eTep.rpy("rad") |
61 | 48 |
|
| 49 | +# # Form error vector |
| 50 | +# e = np.r_[ev, ew] |
62 | 51 |
|
63 | | -# def _angle_axis(T, Td): |
64 | | -# d = base.transl(Td) - base.transl(T) |
65 | | -# R = base.t2r(Td) @ base.t2r(T).T |
66 | | -# li = np.r_[R[2, 1] - R[1, 2], R[0, 2] - R[2, 0], R[1, 0] - R[0, 1]] |
| 52 | +# # Desired end-effector velocity |
| 53 | +# v = gain * e |
67 | 54 |
|
68 | | -# if base.iszerovec(li): |
69 | | -# # diagonal matrix case |
70 | | -# if np.trace(R) > 0: |
71 | | -# # (1,1,1) case |
72 | | -# a = np.zeros((3,)) |
73 | | -# else: |
74 | | -# a = np.pi / 2 * (np.diag(R) + 1) |
| 55 | +# if np.sum(np.abs(e)) < threshold: |
| 56 | +# arrived = True |
75 | 57 | # else: |
76 | | -# # non-diagonal matrix case |
77 | | -# ln = base.norm(li) |
78 | | -# a = math.atan2(ln, np.trace(R) - 1) * li / ln |
| 58 | +# arrived = False |
| 59 | + |
| 60 | +# return v, arrived |
| 61 | + |
| 62 | + |
| 63 | +def _angle_axis(T, Td): |
| 64 | + e = np.zeros(6) |
| 65 | + e[:3] = Td.t - T.t |
| 66 | + R = Td.R @ T.R.T |
| 67 | + li = np.array([R[2, 1] - R[1, 2], R[0, 2] - R[2, 0], R[1, 0] - R[0, 1]]) |
| 68 | + |
| 69 | + if base.iszerovec(li): |
| 70 | + # diagonal matrix case |
| 71 | + if np.trace(R) > 0: |
| 72 | + # (1,1,1) case |
| 73 | + a = np.zeros((3,)) |
| 74 | + else: |
| 75 | + a = np.pi / 2 * (np.diag(R) + 1) |
| 76 | + else: |
| 77 | + # non-diagonal matrix case |
| 78 | + ln = base.norm(li) |
| 79 | + a = math.atan2(ln, np.trace(R) - 1) * li / ln |
| 80 | + |
| 81 | + e[3:] = a |
| 82 | + |
| 83 | + return e |
79 | 84 |
|
80 | | -# return np.r_[d, a] |
| 85 | + |
| 86 | +def p_servo(wTe, wTep, gain=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0], threshold=0.1): |
| 87 | + if not isinstance(wTe, SE3): |
| 88 | + wTe = SE3(wTe) |
| 89 | + |
| 90 | + if not isinstance(wTep, SE3): |
| 91 | + wTep = SE3(wTep) |
| 92 | + |
| 93 | + k = np.diag(gain) |
| 94 | + |
| 95 | + e = _angle_axis(wTe, wTep) |
| 96 | + |
| 97 | + v = k @ e |
| 98 | + |
| 99 | + arrived = True if np.sum(np.abs(e)) < threshold else False |
| 100 | + |
| 101 | + print(np.sum(np.abs(e))) |
| 102 | + |
| 103 | + return v, arrived |
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