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Multi-Robot Patrol Algorithm with Distributed Coordination and Consciousness of the Base Station's Situation Awareness

Kazuho Kobayashi, Seiya Ueno, Takehiro Higuchi

TL;DR

An algorithm: Local Reactive (LR) for multi-robot patrolling to satisfy both needs: patrol efficiently and provide humans with better situation awareness to enhance system predictability.

Abstract

Multi-robot patrolling is the potential application for robotic systems to survey wide areas efficiently without human burdens and mistakes. However, such systems have few examples of real-world applications due to their lack of human predictability. This paper proposes an algorithm: Local Reactive (LR) for multi-robot patrolling to satisfy both needs: (i)patrol efficiently and (ii)provide humans with better situation awareness to enhance system predictability. Each robot operating according to the proposed algorithm selects its patrol target from the local areas around the robot's current location by two requirements: (i)patrol location with greater need, (ii)report its achievements to the base station. The algorithm is distributed and coordinates the robots without centralized control by sharing their patrol achievements and degree of need to report to the base station. The proposed algorithm performed better than existing algorithms in both patrolling and the base station's situation awareness.

Multi-Robot Patrol Algorithm with Distributed Coordination and Consciousness of the Base Station's Situation Awareness

TL;DR

An algorithm: Local Reactive (LR) for multi-robot patrolling to satisfy both needs: patrol efficiently and provide humans with better situation awareness to enhance system predictability.

Abstract

Multi-robot patrolling is the potential application for robotic systems to survey wide areas efficiently without human burdens and mistakes. However, such systems have few examples of real-world applications due to their lack of human predictability. This paper proposes an algorithm: Local Reactive (LR) for multi-robot patrolling to satisfy both needs: (i)patrol efficiently and (ii)provide humans with better situation awareness to enhance system predictability. Each robot operating according to the proposed algorithm selects its patrol target from the local areas around the robot's current location by two requirements: (i)patrol location with greater need, (ii)report its achievements to the base station. The algorithm is distributed and coordinates the robots without centralized control by sharing their patrol achievements and degree of need to report to the base station. The proposed algorithm performed better than existing algorithms in both patrolling and the base station's situation awareness.
Paper Structure (13 sections, 4 equations, 5 figures, 1 table, 2 algorithms)

This paper contains 13 sections, 4 equations, 5 figures, 1 table, 2 algorithms.

Table of Contents

  1. INTRODUCTION
  2. PROBLEM SETTINGS
  3. Mission
  4. Robots
  5. Performance metric
  6. PROPOSED ALGORITHM
  7. Robotic assumption and its sharing
  8. Target selection
  9. SIMULATIONS
  10. Compared Algorithm
  11. Configurations
  12. Results
  13. CONCLUSION

Figures (5)

  • Figure 1: Screenshot of the simulated patrol mission ($N=8$). The black, cyan circles, and lines represent the base station, robots, and connections, respectively. Grid color indicates the ground truth of idleness: darker colors signify higher idleness.
  • Figure 2: Box plot of Graph Idleness: $I_G$ by all ten trials
  • Figure 3: Box plot of Worst Idleness: $I_W$ by all ten trials
  • Figure 4: Box plot of Mean SA delay: $D_{\mathrm{MSA}}$ by all ten trials
  • Figure 5: Box plot of Worst SA delay: $D_{\mathrm{WSA}}$ by all ten trials