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Multi Agent Pathfinding for Noise Restricted Hybrid Fuel Unmanned Aerial Vehicles

Published 26 Mar 2024 in math.OC and cs.RO | (2403.17849v1)

Abstract: Multi Agent Path Finding (MAPF) seeks the optimal set of paths for multiple agents from respective start to goal locations such that no paths conflict. We address the MAPF problem for a fleet of hybrid-fuel unmanned aerial vehicles which are subject to location-dependent noise restrictions. We solve this problem by searching a constraint tree for which the subproblem at each node is a set of shortest path problems subject to the noise and fuel constraints and conflict zone avoidance. A labeling algorithm is presented to solve this subproblem, including the conflict zones which are treated as dynamic obstacles. We present the experimental results of the algorithms for various graph sizes and number of agents.

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References (21)
  1. P. Yedavalli and J. Mooberry, “An assessment of public perception of urban air mobility (UAM),” Airbus UTM: Defining Future Skies, 2019.
  2. A. Townsend, I. N. Jiya, C. Martinson, D. Bessarabov, and R. Gouws, “A comprehensive review of energy sources for unmanned aerial vehicles, their shortfalls and opportunities for improvements,” Heliyon, vol. 6, no. 11, p. e05285, 2020. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2405844020321289
  3. D. Scott, S. G. Manyam, I. E. Weintraub, D. W. Casbeer, and M. Kumar, “Noise aware path planning and power management of hybrid fuel uavs,” arXiv:2402.17708, 2024.
  4. R. Stern, N. Sturtevant, A. Felner, S. Koenig, H. Ma, T. Walker, J. Li, D. Atzmon, L. Cohen, T. Kumar et al., “Multi-agent pathfinding: Definitions, variants, and benchmarks,” in Proceedings of the International Symposium on Combinatorial Search, vol. 10, no. 1, 2019, pp. 151–158.
  5. J. E. Hopcroft, J. T. Schwartz, and M. Sharir, “On the complexity of motion planning for multiple independent objects; pspace-hardness of the” warehouseman’s problem”,” The international journal of robotics research, vol. 3, no. 4, pp. 76–88, 1984.
  6. J. H. Reif, “Complexity of the mover’s problem and generalizations,” pp. 421–427, 1979.
  7. P. Surynek, “An optimization variant of multi-robot path planning is intractable,” in Proceedings of the AAAI conference on artificial intelligence, vol. 24, no. 1, 2010, pp. 1261–1263.
  8. J. Yu and S. LaValle, “Structure and intractability of optimal multi-robot path planning on graphs,” in Proceedings of the AAAI Conference on Artificial Intelligence, vol. 27, no. 1, 2013, pp. 1443–1449.
  9. T. Standley, “Finding optimal solutions to cooperative pathfinding problems,” in Proceedings of the AAAI Conference on Artificial Intelligence, vol. 24, no. 1, 2010, pp. 173–178.
  10. G. Sharon, R. Stern, M. Goldenberg, and A. Felner, “The increasing cost tree search for optimal multi-agent pathfinding,” Artificial intelligence, vol. 195, pp. 470–495, 2013.
  11. G. Sharon, R. Stern, A. Felner, and N. R. Sturtevant, “Conflict-based search for optimal multi-agent pathfinding,” Artificial Intelligence, vol. 219, pp. 40–66, 2015.
  12. M. Barer, G. Sharon, R. Stern, and A. Felner, “Suboptimal variants of the conflict-based search algorithm for the multi-agent pathfinding problem,” in Proceedings of the International Symposium on Combinatorial Search, vol. 5, no. 1, 2014, pp. 19–27.
  13. D. Scott, S. G. Manyam, D. W. Casbeer, M. Kumar, M. J. Rothenberger, and I. E. Weintraub, “Power management for noise aware path planning of hybrid uavs,” in 2022 American Control Conference (ACC).   IEEE, 2022, pp. 4280–4285.
  14. S. G. Manyam, D. W. Casbeer, S. Darbha, I. E. Weintraub, and K. Kalyanam, “Path planning and energy management of hybrid air vehicles for urban air mobility,” IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 10 176–10 183, 2022.
  15. D. Scott, S. G. Manyam, D. W. Casbeer, M. Kumar, I. E. Weintraub, and M. J. Rothenberger, “Development of linear battery model for path planning with mixed integer linear programming: Simulated and experimental validation,” arXiv preprint arXiv:2211.09899, 2022.
  16. D. Scott, S. G. Manyam, D. W. Casbeer, M. Kumar, and I. E. Weintraub, “Optimal generator policy for hybrid fuel uav under airspace noise restrictions,” to be published in MECC 2023, 2023.
  17. J. H. Jadischke, M. Wolff, J. Zumberge, B. Hencey, and A. Ngo, “Optimal route planning and power management for hybrid uav using a* algorithm,” in AIAA AVIATION 2023 Forum, 2023, p. 4508.
  18. E. W. Dijkstra et al., “A note on two problems in connexion with graphs,” Numerische mathematik, vol. 1, no. 1, pp. 269–271, 1959.
  19. P. E. Hart, N. J. Nilsson, and B. Raphael, “A formal basis for the heuristic determination of minimum cost paths,” IEEE transactions on Systems Science and Cybernetics, vol. 4, no. 2, pp. 100–107, 1968.
  20. J. Bezanson, S. Karpinski, V. B. Shah, and A. Edelman, “Julia: A fast dynamic language for technical computing,” arXiv preprint arXiv:1209.5145, 2012.
  21. S. Choudhury, K. Solovey, M. J. Kochenderfer, and M. Pavone, “Efficient large-scale multi-drone delivery using transit networks,” Journal of Artificial Intelligence Research, vol. 70, pp. 757–788, 2021.

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