SPROOCMay 7, 2018

A Generalized Matrix Inverse with Applications to Robotic Systems

arXiv:1806.01776v17 citations
Originality Synthesis-oriented
AI Analysis

This addresses the need for reliable and invariant control in robotics, though it appears incremental as it builds on a recently introduced inverse.

The paper tackles the problem of ensuring performance consistency in robotic control systems across different coordinate frames and units by introducing a generalized matrix inverse, which guarantees robustness in underdetermined and overdetermined systems.

It is well-understood that the robustness of mechanical and robotic control systems depends critically on minimizing sensitivity to arbitrary application-specific details whenever possible. For example, if a system is defined and performs well in one particular Euclidean coordinate frame then it should be expected to perform identically if that coordinate frame is arbitrarily rotated or scaled. Similarly, the performance of the system should not be affected if its key parameters are all consistently defined in metric units or in imperial units. In this paper we show that a recently introduced generalized matrix inverse permits performance consistency to be rigorously guaranteed in control systems that require solutions to underdetermined and/or overdetermined systems of equations.

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