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REACT: Multi Robot Energy-Aware Orchestrator for Indoor Search and Rescue Critical Tasks

Fabio Maresca, Arnau Romero, Carmen Delgado, Vincenzo Sciancalepore, Josep Paradells, Xavier Costa-Pérez

TL;DR

This paper proposes REACT, a smart energy-aware orchestrator that optimizes the exploration phase, ensuring prolonged operational time and effective area coverage and significantly improves the efficiency and reliability of search and rescue missions in complex indoor environments.

Abstract

Smart factories enhance production efficiency and sustainability, but emergencies like human errors, machinery failures and natural disasters pose significant risks. In critical situations, such as fires or earthquakes, collaborative robots can assist first-responders by entering damaged buildings and locating missing persons, mitigating potential losses. Unlike previous solutions that overlook the critical aspect of energy management, in this paper we propose REACT, a smart energy-aware orchestrator that optimizes the exploration phase, ensuring prolonged operational time and effective area coverage. Our solution leverages a fleet of collaborative robots equipped with advanced sensors and communication capabilities to explore and navigate unknown indoor environments, such as smart factories affected by fires or earthquakes, with high density of obstacles. By leveraging real-time data exchange and cooperative algorithms, the robots dynamically adjust their paths, minimize redundant movements and reduce energy consumption. Extensive simulations confirm that our approach significantly improves the efficiency and reliability of search and rescue missions in complex indoor environments, improving the exploration rate by 10% over existing methods and reaching a map coverage of 97% under time critical operations, up to nearly 100% under relaxed time constraint.

REACT: Multi Robot Energy-Aware Orchestrator for Indoor Search and Rescue Critical Tasks

TL;DR

This paper proposes REACT, a smart energy-aware orchestrator that optimizes the exploration phase, ensuring prolonged operational time and effective area coverage and significantly improves the efficiency and reliability of search and rescue missions in complex indoor environments.

Abstract

Smart factories enhance production efficiency and sustainability, but emergencies like human errors, machinery failures and natural disasters pose significant risks. In critical situations, such as fires or earthquakes, collaborative robots can assist first-responders by entering damaged buildings and locating missing persons, mitigating potential losses. Unlike previous solutions that overlook the critical aspect of energy management, in this paper we propose REACT, a smart energy-aware orchestrator that optimizes the exploration phase, ensuring prolonged operational time and effective area coverage. Our solution leverages a fleet of collaborative robots equipped with advanced sensors and communication capabilities to explore and navigate unknown indoor environments, such as smart factories affected by fires or earthquakes, with high density of obstacles. By leveraging real-time data exchange and cooperative algorithms, the robots dynamically adjust their paths, minimize redundant movements and reduce energy consumption. Extensive simulations confirm that our approach significantly improves the efficiency and reliability of search and rescue missions in complex indoor environments, improving the exploration rate by 10% over existing methods and reaching a map coverage of 97% under time critical operations, up to nearly 100% under relaxed time constraint.

Paper Structure

This paper contains 12 sections, 2 equations, 8 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related Works
  3. REACT: Concept, System and Architecture
  4. High-level Orchestrator
  5. Real-time Orchestrator
  6. Robots-plane
  7. Interaction among layers
  8. Performance Evaluation
  9. Scenario setup
  10. Single-Robot Evaluation
  11. Multi-Robot Evaluation
  12. Conclusions and Future Work

Figures (8)

  • Figure 1: Smart Factory Multi Robot SAR scenario.
  • Figure 2: REACT architecture: components, technologies used, interfaces and communication links.
  • Figure 3: The sequence diagram highlights the exchange of messages among the three layers within a time frame reserved to explore the current area. The frequency of occurrence is emulated with example timestamps ts.
  • Figure 4: Battery SOC and Coverage for 1 robot using OROS and REACT. The maximum Operation time is T=240. "Battery Sens. ON" refers to a non-optimized management of the sensors, keeping them always ON.
  • Figure 5: Trajectory performed by 1 robot, deploying different methods.
  • ...and 3 more figures