An Optimization Approach for a Robust and Flexible Control in Collaborative Applications

TL;DR

This paper presents a control architecture for human-robot collaboration that ensures system stability and high flexibility by combining energy tank-based admittance control with control barrier functions, validated through experiments.

Contribution

It introduces a novel control framework that enhances robot flexibility and stability in dynamic collaborative environments, integrating energy tanks and barrier functions.

Findings

Successful experimental validation on a collaborative robot

Enhanced system robustness and reactivity in variable conditions

Maintained stability during physical interactions

Abstract

In Human-Robot Collaboration, the robot operates in a highly dynamic environment. Thus, it is pivotal to guarantee the robust stability of the system during the interaction but also a high flexibility of the robot behavior in order to ensure safety and reactivity to the variable conditions of the collaborative scenario. In this paper we propose a control architecture capable of maximizing the flexibility of the robot while guaranteeing a stable behavior when physically interacting with the environment. This is achieved by combining an energy tank based variable admittance architecture with control barrier functions. The proposed architecture is experimentally validated on a collaborative robot.