Path Planning of AUV Swarms Using a Bio-inspired Multi-Agent System
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Abstract
This paper uses a multi-agent system (MAS) as the bioinformatics-inspired technique for guiding a team of autonomous underwater vehicles (AUVs) toward the desired destination. An individual AUV is designated as an agent connected by a communication network and assumes full communication. Here, each AUV estimates the position of its neighbor AUVs while moving toward the destination. The proposed multi-AUV system consists of a leader AUV and five follower AUVs. A distributed path consensus (DPC) is proposed to ensure the neighboring agent AUVs maintain a predefined distance between each other while moving toward the predefined destination. Due to the proposed distance constraint between neighboring agents, AUVs stay at a safe distance from each other while maintaining underwater communication using interactive switching topology. The performance of the optimized path is obtained using MATLAB simulation. The proposed algorithm is applied in both, formation using the desired shape, and trajectory tracking, and found to be globally asymptotically stable. The results of the simulation confirm that each agent switches from one state to another and progress over time until the desired coordinated shape is achieved without inter-vehicular collision. The proposed method solves coordination problems among multiple AUVs and increases the coverage of underwater missions like oceanographic surveys.
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References
T. I. Fossen, Guidance and Control of Ocean Vehicles. Chichester, UK: John Wiley & Sons, 1994, pp. 6–54.
L. Durica, B. Micieta, P. Bubenik, and V. Binasova, “Manufacturing multi-agent system with bio-inspired techniques: CODESA-prime,” MM Science Journal, vol. 2015, pp. 829–837, Dec. 2015.
B. Das, B. Subudhi, and B. B. Pati, “Formation control of underwater vehicles using multi agent system,” Archives of Control Sciences, vol. 30, no. 2, pp. 365–384, 2020.
Y. Deng, P.-P. J. Beaujean, E. An, and E. Carlson, “Task allocation and path planning for collaborative autonomous underwater vehicles operating through an underwater acoustic network,” Journal of Robotics, vol. 2013, 2013, Art. no. 483095.
B. Das, B. Subudhi, and B. B. Pati, “Employing nonlinear observer for formation control of AUVs under communication constraints,” International Journal of Intelligent Unmanned Systems, vol. 3, no. 2/3, pp. 122–155, 2015.
B. Das, B. Subudhi, and B. B. Pati, “Co-operative control of a team of autonomous underwater vehicles in an obstacle-rich environment,” Journal of Marine Engineering & Technology, vol. 15, no. 3, pp. 135–151, 2016.
B. Das, B. Subudhi, and B. B. Pati, “Co-operative control coordination of a team of underwater vehicles with communication constraints,” Transactions of the Institute of Measurement and Control, vol. 38, no. 4, pp. 463–481, Apr. 2016.
Z. Zuo, M. Defoort, B. Tian, and Z. Ding, “Distributed consensus observer for multiagent systems with high-order integrator dynamics,” IEEE Transactions on Automatic Control, vol. 65, no. 4, pp. 1771–1778, Apr. 2020.
M. Chen and D. Zhu, “A workload balanced algorithm for task assignment and path planning of inhomogeneous autonomous underwater vehicle system,” IEEE Transactions on Cognitive and Developmental Systems, vol. 11, no. 4, pp. 483–493, Dec. 2019.
S. Ul’yanov and N. Maksimkin, “Software toolbox for analysis and design of nonlinear control systems and its application to multi-AUV path-following control,” in 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2017, pp. 1032–1037.
R. Olfati-Saber, J. A. Fax, and R. M. Murray, “Consensus and cooperation in networked multi-agent systems,” Proceedings of the IEEE, vol. 95, no. 1, pp. 215–233, Jan. 2007.
P. Szymak and T. Praczyk, “Control systems of underwater vehicles in multi-agent system of underwater inspection,” in Proceedings of the 11th WSEAS international conference on automatic control, modelling and simulation (ACMOS’09), 2009, pp. 153–156.
H. Yang and F. Zhang, “Geometric formation control for autonomous underwater vehicles,” in 2010 IEEE International Conference on Robotics and Automation, 2010, pp. 4288–4293.
X. Q. Bian, T. Chen, J. Zhou, and Z. Yan, “Research of autonomous control based on multi-agent for AUV,” in 2009 International Workshop on Intelligent Systems and Applications, 2009.
Z. Hu, C. Ma, L. Zhang, A. Halme, T. Hayat, and B. Ahmad, “Formation control of impulsive networked autonomous underwater vehicles under fixed and switching topologies,” Neurocomputing, vol. 147, pp. 291–298, Jan. 2015.
C. Viel, “Control law and state estimators design for multi-agent system with reduction of communications by event-triggered approach,” Ph.D. dissertation, Automatic Control Engineering, Université Paris-Saclay, Paris, France, 2017.
M. R. Bharamagoudra, S. S. Manvi, and B. Gonen, “Event driven energy depth and channel aware routing for underwater acoustic sensor networks: Agent oriented clustering based approach,” Computers & Electrical Engineering, vol. 58, pp. 1–19, Feb. 2017.
Z. Gallehdari, N. Meskin, and K. Khorasani, “Distributed reconfigurable control strategies for switching topology networked multi-agent systems,” ISA Transactions, vol. 71, pp. 51–67, Nov. 2017.
R. Jurdak, A. Elfes, B. Kusy, A. Tews, W. Hu, E. Hernandez, N. Kottege, and P. Sikka, “Autonomous surveillance for biosecurity,” Trends in Biotechnology, vol. 33, no. 4, pp. 201–207, Apr. 2015.
H. G. de Marina, M. Cao, and B. Jayawardhana, “Controlling rigid formations of mobile agents under inconsistent measurements,” IEEE Transactions on Robotics, vol. 31, no. 1, pp. 31–39, Feb. 2015.
J. Fu and J. Wang, “Fixed-time coordinated tracking for second-order multi-agent systems with bounded input uncertainties,” Systems & Control Letters, vol. 93, pp. 1–12, Jul. 2016.
S. Bhattacharya, M. Likhachev, and V. Kumar, “Distributed path consensus algorithm,” University of Pennsylvania, Philadelphia, PA, USA, Technical report. MS-CIS-10-07, 2010.
S. Bhattacharya, M. Likhachev, and V. Kumar, “Multi-agent path planning with multiple tasks and distance constraints,” in 2010 IEEE International Conference on Robotics and Automation, 2010, pp. 953–959.
M. K. Rizwan, B. Das, and B. B. Pati, “A criterion based adaptive RSIC scheme in underwater communication,” Journal of Systems Engineering and Electronics, vol. 32, no. 2, pp. 408–416, Apr. 2021.
B. Das, B. Subudhi, and B. B. Pati, “Cooperative formation control of autonomous underwater vehicles: An overview,” International Journal of Automation and Computing, vol. 13, no. 3, pp. 199–225, Jun. 2016.
B. Das, B. Subudhi, and B. B. Pati, “Adaptive sliding mode formation control of multiple underwater robots,” Archives of Control Sciences, vol. 24, no. 4, pp. 515–543, Dec. 2014.