CoHaptics: Development of Human-Robot Collaborative System with Forearm-worn Haptic Display to Increase Safety in Future Factories

TL;DR

This paper presents CoHaptics, a human-robot collaborative system with a forearm-worn haptic display, enhancing safety by increasing safe distances and reducing collision paths through haptic feedback and a novel collision avoidance algorithm.

Contribution

It introduces a new framework combining haptic feedback, wearable motion capture, and an APF-based collision avoidance algorithm to improve safety in human-robot collaboration.

Findings

Safe distance increased by 4.1 cm with haptic feedback.

Robot path reduced by 81% during collision avoidance.

Haptic feedback improves human response and safety in collaboration.

Abstract

Complex tasks require human collaboration since robots do not have enough dexterity. However, robots are still used as instruments and not as collaborative systems. We are introducing a framework to ensure safety in a human-robot collaborative environment. The system is composed of a haptic feedback display, low-cost wearable mocap, and a new collision avoidance algorithm based on the Artificial Potential Fields (APF). Wearable optical motion capturing system enables tracking the human hand position with high accuracy and low latency on large working areas. This study evaluates whether haptic feedback improves safety in human-robot collaboration. Three experiments were carried out to evaluate the performance of the proposed system. The first one evaluated human responses to the haptic device during interaction with the Robot Tool Center Point (TCP). The second experiment analyzed human-robot behavior during an imminent collision. The third experiment evaluated the system in a collaborative activity in a shared working environment. This study had shown that when haptic feedback in the control loop was included, the safe distance (minimum robot-obstacle distance) increased by 4.1 cm from 12.39 cm to 16.55 cm, and the robot's path, when the collision avoidance algorithm was activated, was reduced by 81%.