Human–Robot Collaboration in Smart Manufacturing: Robot Reactive Behavior Intelligence

Author:

Nicora Matteo Lavit1,Ambrosetti Roberto2,Wiens Gloria J.3,Fassi Irene4

Affiliation:

1. Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council of Italy, Via Previati 1/E, Lecco 23900, Italy

2. Department of Mechanical Engineering, Politecnico di Milano, Milano 20156, Italy

3. Department of Mechanical and, Aerospace Engineering, University of Florida, Gainesville, FL 32611-6250

4. Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council of Italy, Via Alfonso Corti 12, Milano 20133, Italy

Abstract

Abstract To enable safe and effective human–robot collaboration (HRC) in smart manufacturing, seamless integration of sensing, cognition, and prediction into the robot controller is critical for real-time awareness, response, and communication inside a heterogeneous environment (robots, humans, and equipment). The specific research objective is to provide the robot Proactive Adaptive Collaboration Intelligence (PACI) and switching logic within its control architecture in order to give the robot the ability to optimally and dynamically adapt its motions, given a priori knowledge and predefined execution plans for its assigned tasks. The challenge lies in augmenting the robot’s decision-making process to have greater situation awareness and to yield smart robot behaviors/reactions when subject to different levels of human–robot interaction, while maintaining safety and production efficiency. Robot reactive behaviors were achieved via cost function-based switching logic activating the best suited high-level controller. The PACI’s underlying segmentation and switching logic framework is demonstrated to yield a high degree of modularity and flexibility. The performance of the developed control structure subjected to different levels of human–robot interactions was validated in a simulated environment. Open-loop commands were sent to the physical e.DO robot to demonstrate how the proposed framework would behave in a real application.

Funder

National Science Foundation

Publisher

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering

Reference17 articles.

1. IFR Press Release;International Federation of Robotics,2019

2. Multi-Objective Approach to HRC Manufacturing Environment;Streitmatter,2019

3. ROS: An Open-Source Robot Operating System;Quigley;ICRA Workshop on Open Source Software,2009

4. Moveit!;Chitta;IEEE Robot. Autom. Mag.,2012

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