Multi-robots Coordination System for Urban Search and Rescue Assistance Based on Supervisory Control Theory

• Published in: Journal of control, automation & electrical systems Vol. 34; no. 3; pp. 484 - 495
• Main Authors: Simon, Marcelo Elias, Baldissera, Fabio Luiz, de Queiroz, Max Hering, Cabral, Felipe Gomes
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2023; Springer Nature B.V
• Subjects: Artificial intelligence; Control; Control and Systems Theory; Control theory; Coordination; Disasters; Electrical Engineering; Engineering; Evacuations & rescues; Mechatronics; Multiple robots; Robotics; Robotics and Automation; Robots; Supervisors; Supervisory control; Unmanned aerial vehicles; USAR; Supervisory control; Deliberative; Multi-robots; Reactive
• ISSN: 2195-3880; 2195-3899
• DOI: 10.1007/s40313-023-00986-7

The application of robots in urban search and rescue (USAR) is a domain receiving increasing attention from the scientific community, although it does not yet grant the requirements for field implementation, such as robustness, reliability, and safety. In this work, we propose a multi-robots coordination system based on the supervisory control theory (SCMCS) divided into two layers: reactive and deliberative. While the reactive layer assures that each robot attains to the critical USAR requirements in face of unexpected events by means of a maximally permissive and nonblocking supervisory control, the deliberative layer coordinates the multi-robots system exploiting heuristics to perform the missions with efficiency. The formal modeling and synthesis of supervisors are applied to a case study based on the international USAR agency procedures. The SCMCS architecture is implemented in a simulated scenario composed of two ground robots and two aerial robots executing USAR missions in a post-disaster scene subject to unexpected events such as robot failures, victims and dangers detection and battery losses. The simulation results show that SCMCS is capable of efficiently coordinating the tasks assigned to multiple robots while guaranteeing critical requirements even in face of the uncertainties of robots and environments in USAR disasters.