rtjademo.m

Robotics TOOLBOX The Toolbox provides many functions that are useful in robotics including such thi

% Copyright (C) 1993-2002, by Peter I. Corke
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% 6/99	change arg to maniplty() to 'yoshikawa'
% $Log: rtjademo.m,v $
% Revision 1.2  2002/04/01 11:47:17  pic
% General cleanup of code: help comments, see also, copyright, remnant dh/dyn
% references, clarification of functions.
%
% $Revision: 1.2 $
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%
% Jacobian and differential motion demonstration
%
% A differential motion can be represented by a 6-element vector with elements
% [dx dy dz drx dry drz]
%
% where the first 3 elements are a differential translation, and the last 3 
% are a differential rotation.  When dealing with infinitisimal rotations, 
% the order becomes unimportant.  The differential motion could be written 
% in terms of compounded transforms
%
% transl(dx,dy,dz) * rotx(drx) * roty(dry) * rotz(drz)
%
% but a more direct approach is to use the function diff2tr()
%
    D = [.1 .2 0 -.2 .1 .1]';
    diff2tr(D)
pause % any key to continue
%
% More commonly it is useful to know how a differential motion in one 
% coordinate frame appears in another frame.  If the second frame is 
% represented by the transform
    T = transl(100, 200, 300) * roty(pi/8) * rotz(-pi/4);
%
% then the differential motion in the second frame would be given by

    DT = tr2jac(T) * D;
    DT'
%
% tr2jac() has computed a 6x6 Jacobian matrix which transforms the differential 
% changes from the first frame to the next.
%
pause % any key to continue

% The manipulator's Jacobian matrix relates differential joint coordinate 
% motion to differential Cartesian motion;
%
% 	dX = J(q) dQ
%
% For an n-joint manipulator the manipulator Jacobian is a 6 x n matrix and
% is used is many manipulator control schemes.  For a 6-axis manipulator like
% the Puma 560 the Jacobian is square
%
% Two Jacobians are frequently used, which express the Cartesian velocity in
% the world coordinate frame,

    q = [0.1 0.75 -2.25 0 .75 0]
    J = jacob0(p560, q)
%
% or the T6 coordinate frame

    J = jacobn(p560, q)
%
% Note the top right 3x3 block is all zero.  This indicates, correctly, that
% motion of joints 4-6 does not cause any translational motion of the robot's
% end-effector.
pause % any key to continue

%
%  Many control schemes require the inverse of the Jacobian.  The Jacobian
% in this example is not singular
    det(J)
%
% and may be inverted
    Ji = inv(J)
pause % any key to continue
%
% A classic control technique is Whitney's resolved rate motion control
%
% dQ/dt = J(q)^-1 dX/dt
%
% where dX/dt is the desired Cartesian velocity, and dQ/dt is the required
% joint velocity to achieve this.
    vel = [1 0 0 0 0 0]'; % translational motion in the X direction
    qvel = Ji * vel;
    qvel'
%
%  This is an alternative strategy to computing a Cartesian trajectory 
% and solving the inverse kinematics.  However like that other scheme, this
% strategy also runs into difficulty at a manipulator singularity where
% the Jacobian is singular.

pause % any key to continue
%
% As already stated this Jacobian relates joint velocity to end-effector 
% velocity expressed in the end-effector reference frame.  We may wish 
% instead to specify the velocity in base or world coordinates.
%
% We have already seen how differential motions in one frame can be translated 
% to another.  Consider the velocity as a differential in the world frame, that
% is, d0X.  We can write
% 	d6X = Jac(T6) d0X
%
    T6 = fkine(p560, q); % compute the end-effector transform
    d6X = tr2jac(T6) * vel; % translate world frame velocity to T6 frame
    qvel = Ji * d6X; % compute required joint velocity as before
    qvel'
%
% Note that this value of joint velocity is quite different to that calculated
% above, which was for motion in the T6 X-axis direction.
pause % any key to continue
%
%  At a manipulator singularity or degeneracy the Jacobian becomes singular.
% At the Puma's `ready' position for instance, two of the wrist joints are
% aligned resulting in the loss of one degree of freedom.  This is revealed by
% the rank of the Jacobian
    rank( jacobn(p560, qr) )
%
% and the singular values are
    svd( jacobn(p560, qr) )
pause % any key to continue
%
% When not actually at a singularity the Jacobian can provide information 
% about how `well-conditioned' the manipulator is for making certain motions,
% and is referred to as `manipulability'.
%
% A number of scalar manipulability measures have been proposed.  One by
% Yoshikawa
    maniplty(p560, q, 'yoshikawa')
%
% is based purely on kinematic parameters of the manipulator.
%
% Another by Asada takes into account the inertia of the manipulator which 
% affects the acceleration achievable in different directions.  This measure 
% varies from 0 to 1, where 1 indicates uniformity of acceleration in all 
% directions
    maniplty(p560, q, 'asada')
%
% Both of these measures would indicate that this particular pose is not well
% conditioned.
pause % any key to continue

% An interesting class of manipulators are those that are redundant, that is,
% they have more than 6 degrees of freedom.  Computing the joint motion for
% such a manipulator is not straightforward.  Approaches have been suggested
% based on the pseudo-inverse of the Jacobian (which will not be square) or
% singular value decomposition of the Jacobian.
%
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