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Human-Robot Perception in Industrial Environments: A Survey.

Andrea Bonci¹, Pangcheng David Cen Cheng², Marina Indri²

¹Dipartimento di Ingegneria dell'Informazione (DII), Università Politecnica delle Marche, 60131 Ancona, Italy.

Sensors (Basel, Switzerland)

|March 6, 2021

Summary

This study surveys sensors for human detection and action recognition in industrial settings. It addresses safety and productivity in human-robot collaboration by analyzing perception techniques for various robotic systems.

Keywords:

3D sensors collision avoidance collision detection human action recognition human-robot collaboration human-robot perception machine vision robot guidance

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Area of Science:

Robotics
Human-Robot Interaction
Industrial Automation

Background:

Industrial environments demand high automation for flexibility and cost-efficiency.
Autonomous and collaborative robots are crucial for adapting to dynamic conditions, including human presence.
Lack of human awareness in shared workspaces poses safety risks and reduces productivity.

Purpose of the Study:

To survey sensory equipment for human detection and action recognition in industrial settings.
To analyze perception techniques and sensors for various robotic systems (fixed-base, collaborative, mobile).
To present proofs of concept for enhanced human perception and interaction in collaborative robotics.

Main Methods:

Literature review of sensors and perception techniques for human detection and action recognition.
Analysis of sensor suitability for different robotic platforms (manipulators, mobile robots).
Development and presentation of two proofs of concept for enhanced human-robot collaboration.

Main Results:

Identified key sensors and perception methods for human detection and action recognition in industrial environments.
Evaluated the applicability of these methods across diverse robotic systems.
Demonstrated practical solutions for human safety (collision avoidance) and collaborative behavior in shared spaces.

Conclusions:

Effective human perception is vital for safe and productive human-robot collaboration in industrial settings.
A range of sensors and techniques can be employed to enhance robot awareness of human presence and intentions.
The presented proofs of concept offer viable pathways for future collaborative robotic applications.