Kinematic Control of Redundant Robots with Online Handling of Variable Generalized Hard Constraints

TL;DR

This paper introduces a generalized algorithm for controlling redundant robots that ensures hard joint and Cartesian constraints are never violated, even when these constraints change dynamically during operation.

Contribution

A unified, online-capable algorithm that manages variable inequality constraints in redundant robot control, improving safety and flexibility in unstructured environments.

Findings

Effective constraint handling demonstrated in simulations

Experimental validation on robotic systems shows robustness

Algorithm maintains primary task fulfillment under constraints

Abstract

We present a generalized version of the Saturation in the Null Space (SNS) algorithm for the task control of redundant robots when hard inequality constraints are simultaneously present both in the joint and in the Cartesian space. These hard bounds should never be violated, are treated equally and in a unified way by the algorithm, and may also be varied, inserted or deleted online. When a joint/Cartesian bound saturates, the robot redundancy is exploited to continue fulfilling the primary task. If no feasible solution exists, an optimal scaling procedure is applied to enforce directional consistency with the original task. Simulation and experimental results on different robotic systems demonstrate the efficiency of the approach. The proposed algorithm can be viewed as a generic platform that is easily applicable to any robotic application in which robots operate in an unstructured environment and online handling of joint and Cartesian constraints is critical.