Abstract
A systematic and general approach to represent functional redundancy is presented. It is shown how this approach allows the freedom provided by functional redundancy to be integrated into the inverse geometric problem for real-time applications and how it can be utilised to improve performance. A set of new iterative solutions to the inverse geometric problem, well suited for kinematically redundant manipulators, is also presented.
Highlights
This paper addresses functional and kinematic redundancy
The transformation from operational to joint space is obtained by the inverse kinematic problem, which finds the joint velocities from the desired end-effector velocities
To illustrate the advantages of the general representation of the freedom provided by the functional redundancy, a sub-optimal approach based on complete path information which does not increase the computation time notably is presented
Summary
This paper addresses functional and kinematic redundancy. Both types of redundancy provide a freedom that should be utilised in order to improve the performance of the manipulator. Some joint space control scheme, independent of the task, can be designed The disadvantage of this approach is that the inverse geometrics is a timeconsuming problem to solve. To illustrate the advantages of the general representation of the freedom provided by the functional redundancy, a sub-optimal approach based on complete path information which does not increase the computation time notably is presented. This approach can be integrated into any inverse geometric/kinematic algorithm and is suitable for real-time applications. The solution is shown for a cost function representing the position and orientation error of the end effector but can be expanded to include a general class of cost functions representing both global and local objectives. An analytic and computationally efficient alternative to the steepest descent is presented
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