Neural leader–follower swarm control algorithm for underwater vehicles

• Published in: Neural computing & applications Vol. 37; no. 24; pp. 19867 - 19893
• Main Author: Praczyk, Tomasz
• Format: Journal Article
• Language: English
• Published: London Springer London 01.08.2025; Springer Nature B.V
• Subjects: Acoustics; Artificial Intelligence; Communications systems; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Control algorithms; Control theory; Cooperation; Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Information sources; Neural networks; Original Article; Probability and Statistics in Computer Science; Radio communications; Sensors; Shoran; Sonar; Telematics; Traffic speed; Trajectories; Underwater vehicles; Vehicles; Autonomous underwater vehicles; Swarm; Neuro-evolution; Recurrent neural networks; Robot control
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-025-11429-6

The paper deals with the problem of controlling a swarm of underwater vehicles where vehicle sensors cannot distinguish swarm vehicles from other objects, for example, obstacles. The paper assumes a leader–follower strategy, according to which a swarm of low-cost follower vehicles equipped only with short-range navigation follows the leader along a desired trajectory defined in 2D space. Although the trajectory is defined in 2D space, vehicles can change the depth at which they move, resulting in a temporary loss of sensor data. The paper also considers the possibility of a hybrid swarm consisting of vehicles with different characteristics and a variable formation in which the vehicles move. The vehicles are controlled using neural networks that determine the direction of movement and speed of vehicles and are supplied with data from sensors with different operation ranges. The effectiveness of the networks was verified in simulation conditions. Verification tests have shown that the vehicles are able to: (i) independently form an organized swarm in the initial phase of the operation, (ii) move in two different formations despite interference affecting the operation of sensors and making it difficult to maintain the formation, (iii) cooperate within one swarm despite differences in the maneuverability of individual swarm members, and (iv) change the mission depth as a group; however, it is recommended to carry out the depth change maneuver only on straight sections of the trajectory.