Seamless Interaction Design with Coexistence and Cooperation Modes for Robust Human-Robot Collaboration

TL;DR

This paper introduces the CoCo system, a human-robot collaboration framework that combines coexistence and cooperation modes for robust industrial task performance, utilizing a human intention tracking algorithm.

Contribution

It presents a novel interaction system that seamlessly switches between coexistence and cooperation modes based on human intention, enhancing collaboration robustness.

Findings

Effective in multi-step assembly task simulation

Enables mode switching based on human intention

Improves robustness of human-robot collaboration

Abstract

A robot needs multiple interaction modes to robustly collaborate with a human in complicated industrial tasks. We develop a Coexistence-and-Cooperation (CoCo) human-robot collaboration system. Coexistence mode enables the robot to work with the human on different sub-tasks independently in a shared space. Cooperation mode enables the robot to follow human guidance and recover failures. A human intention tracking algorithm takes in both human and robot motion measurements as input and provides a switch on the interaction modes. We demonstrate the effectiveness of CoCo system in a use case analogous to a real world multi-step assembly task.