Bidirectional Communication Control for Human-Robot Collaboration

TL;DR

This paper introduces a novel control architecture for human-robot collaboration that uses control barrier functions and bidirectional communication to adapt tasks based on the robot's skills and limits, enhancing mutual understanding.

Contribution

It presents a new communication control architecture that enables robots to assess their capabilities and propose alternatives, improving human-robot collaboration.

Findings

Effective communication of robot limits and skills

Ability to propose task alternatives dynamically

Enhanced collaboration through bidirectional communication

Abstract

A fruitful collaboration is based on the mutual knowledge of each other skills and on the possibility of communicating their own limits and proposing alternatives to adapt the execution of a task to the capabilities of the collaborators. This paper aims at reproducing such a scenario in a human-robot collaboration setting by proposing a novel communication control architecture. Exploiting control barrier functions, the robot is made aware of its (dynamic) skills and limits and, thanks to a local predictor, it is able to assess if it is possible to execute a requested task and, if not, to propose alternative by relaxing some constraints. The controller is interfaced with a communication infrastructure that enables human and robot to set up a bidirectional communication about the task to execute and the human to take an informed decision on the behavior of the robot. A comparative experimental validation is proposed.