|
1 | | -#MANIPLTY Manipulability measure |
2 | | -# |
3 | | -# M = MANIPLTY(ROBOT, Q) |
4 | | -# M = MANIPLTY(ROBOT, Q, WHICH) |
5 | | -# |
6 | | -# Computes the manipulability index for the manipulator at the given pose. |
7 | | -# |
8 | | -# For an n-axis manipulator Q may be an n-element vector, or an m x n |
9 | | -# joint space trajectory. |
10 | | -# |
11 | | -# If Q is a vector MANIPLTY returns a scalar manipulability index. |
12 | | -# If Q is a matrix MANIPLTY returns a column vector of manipulability |
13 | | -# indices for each pose specified by Q. |
14 | | -# |
15 | | -# The argument WHICH can be either 'yoshikawa' (default) or 'asada' and |
16 | | -# selects one of two manipulability measures. |
17 | | -# Yoshikawa's manipulability measure gives an indication of how far |
18 | | -# the manipulator is from singularities and thus able to move and |
19 | | -# exert forces uniformly in all directions. |
20 | | -# |
21 | | -# Asada's manipulability measure is based on the manipulator's |
22 | | -# Cartesian inertia matrix. An n-dimensional inertia ellipsoid |
23 | | -# X' M(q) X = 1 |
24 | | -# gives an indication of how well the manipulator can accelerate |
25 | | -# in each of the Cartesian directions. The scalar measure computed |
26 | | -# here is the ratio of the smallest/largest ellipsoid axis. Ideally |
27 | | -# the ellipsoid would be spherical, giving a ratio of 1, but in |
28 | | -# practice will be less than 1. |
29 | | -# |
30 | | -# See also: INERTIA, JACOB0. |
| 1 | +""" |
| 2 | +Robot manipulability operations. |
| 3 | +
|
| 4 | +@author: Peter Corke |
| 5 | +@copyright: Peter Corke |
| 6 | +""" |
31 | 7 |
|
32 | | -# MOD HISTORY |
33 | | -# 4/99 object support, matlab local functions |
34 | | -# 6/99 change switch to allow abbreviations of measure type |
35 | | -# $Log: maniplty.m,v $ |
36 | | -# Revision 1.2 2002/04/01 11:47:14 pic |
37 | | -# General cleanup of code: help comments, see also, copyright, remnant dh/dyn |
38 | | -# references, clarification of functions. |
39 | | -# |
40 | | -# $Revision: 1.2 $ |
41 | 8 |
|
42 | | -# Copyright (C) 1993-2002, by Peter I. Corke |
43 | 9 |
|
44 | 10 | from numpy import * |
45 | 11 | from jacob0 import * |
|
48 | 14 | from numrows import * |
49 | 15 |
|
50 | 16 | def maniplty(robot, q, which = 'yoshikawa'): |
51 | | - n = robot.n |
| 17 | + ''' |
| 18 | + MANIPLTY Manipulability measure |
| 19 | +
|
| 20 | + - M = MANIPLTY(ROBOT, Q) |
| 21 | + - M = MANIPLTY(ROBOT, Q, WHICH) |
| 22 | +
|
| 23 | + Computes the manipulability index for the manipulator at the given pose. |
| 24 | +
|
| 25 | + For an n-axis manipulator Q may be an n-element vector, or an m x n |
| 26 | + joint space trajectory. |
| 27 | +
|
| 28 | + If Q is a vector MANIPLTY returns a scalar manipulability index. |
| 29 | + If Q is a matrix MANIPLTY returns a column vector of manipulability |
| 30 | + indices for each pose specified by Q. |
| 31 | +
|
| 32 | + The argument WHICH can be either 'yoshikawa' (default) or 'asada' and |
| 33 | + selects one of two manipulability measures. |
| 34 | + Yoshikawa's manipulability measure gives an indication of how far |
| 35 | + the manipulator is from singularities and thus able to move and |
| 36 | + exert forces uniformly in all directions. |
| 37 | +
|
| 38 | + Asada's manipulability measure is based on the manipulator's |
| 39 | + Cartesian inertia matrix. An n-dimensional inertia ellipsoid |
| 40 | + X' M(q) X = 1 |
| 41 | + gives an indication of how well the manipulator can accelerate |
| 42 | + in each of the Cartesian directions. The scalar measure computed |
| 43 | + here is the ratio of the smallest/largest ellipsoid axis. Ideally |
| 44 | + the ellipsoid would be spherical, giving a ratio of 1, but in |
| 45 | + practice will be less than 1. |
| 46 | +
|
| 47 | + @see: inertia, jacob0 |
| 48 | + ''' |
| 49 | + n = robot.n |
52 | 50 | q = mat(q) |
53 | 51 | w = array([]) |
54 | | - if which == 'yoshikawa' or which == 'yoshi' or which == 'y': |
| 52 | + if 'yoshikawa'.startswith(which): |
55 | 53 | if numrows(q)==1: |
56 | 54 | return yoshi(robot,q) |
57 | 55 | for Q in q: |
58 | 56 | w = concatenate((w,array([yoshi(robot,Q)]))) |
59 | | - if which == 'asada' or which == 'a': |
| 57 | + elif 'asada'.startswith(which): |
60 | 58 | if numrows(q)==1: |
61 | 59 | return asada(robot,q) |
62 | 60 | for Q in q: |
|
0 commit comments