Motion Control of Redundant Robots with Generalised Inequality Constraints

TL;DR

This paper introduces an enhanced SNS algorithm for redundant robot motion control that manages joint and Cartesian constraints simultaneously, ensuring task feasibility through a unified inequality handling approach.

Contribution

It extends the SNS algorithm to incorporate Cartesian box constraints with equal priority, improving redundancy resolution at the velocity level.

Findings

Effective constraint management in simulation

Maintains task feasibility under multiple bounds

Applicable to 6R planar robot

Abstract

We present an improved version of the Saturation in the Null Space (SNS) algorithm for redundancy resolution at the velocity level. In addition to hard bounds on joint space motion, we consider also Cartesian box constraints that cannot be violated at any time. The modified algorithm combines all bounds into a single augmented generalised vector and gives equal, highest priority to all inequality constraints. When needed, feasibility of the original task is enforced by the SNS task scaling procedure. Simulation results are reported for a 6R planar robot.