Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
153 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Multi-Robot Patrol Algorithm with Distributed Coordination and Consciousness of the Base Station's Situation Awareness (2307.08966v2)

Published 18 Jul 2023 in cs.RO and cs.MA

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.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (11)
  1. M. Schranz, M. Umlauft, M. Sende, and W. Elmenreich, “Swarm Robotic Behaviors and Current Applications,” Frontiers in Robotics and AI, vol. 7, no. 36, 2020.
  2. D. Carrillo-Zapata, E. Milner, J. Hird, G. Tzoumas, P. J. Vardanega, M. Sooriyabandara, M. Giuliani, A. F. Winfield, and S. Hauert, “Mutual Shaping in Swarm Robotics: User Studies in Fire and Rescue, Storage Organization, and Bridge Inspection,” Frontiers in Robotics and AI, vol. 7, no. 53, apr 2020.
  3. N. R. Gans and J. G. Rogers, “Cooperative Multirobot Systems for Military Applications,” Current Robotics Reports, vol. 2, no. 1, pp. 105–111, 2021.
  4. M. R. Endsley, “Design and Evaluation for Situation Awareness Enhancement,” Proceedings of the Human Factors Society Annual Meeting, vol. 32, no. 2, pp. 97–101, oct 1988.
  5. J. Banfi, N. Basilico, and F. Amigoni, “Minimizing communication latency in multirobot situation-aware patrolling,” in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, pp. 616–622.
  6. J. Scherer and B. Rinner, “Multi-Robot Patrolling with Sensing Idleness and Data Delay Objectives,” Journal of Intelligent and Robotic Systems, vol. 99, no. 3, pp. 949–967, 2020.
  7. L. Huang, M. Zhou, K. Hao, and E. Hou, “A survey of multi-robot regular and adversarial patrolling,” IEEE/CAA Journal of Automatica Sinica, vol. 6, no. 4, pp. 894–903, 2019.
  8. A. Machado, G. Ramalho, J.-D. Zucker, and A. Drogoul, “Multi-agent Patrolling: An Empirical Analysis of Alternative Architectures,” in Multi-Agent-Based Simulation II, 2003, pp. 155–170.
  9. C. Yan and T. Zhang, “Multi-robot patrol: A distributed algorithm based on expected idleness,” International Journal of Advanced Robotic Systems, vol. 13, no. 6, pp. 1–12, nov 2016.
  10. A. Farinelli, L. Iocchi, and D. Nardi, “Distributed on-line dynamic task assignment for multi-robot patrolling,” Autonomous Robots, vol. 41, no. 6, pp. 1321–1345, 2017.
  11. K. Kobayashi, T. Higuchi, and S. Ueno, “Hierarchical and Distributed Patrol Strategy for Robotic Swarms with Continuous Connectivity,” in Proceedings of the Joint Symposium of AROB-ISBC-SWARM2023, 2023, pp. 1491–1496.
Citations (2)

Summary

We haven't generated a summary for this paper yet.