Affiliation:
1. Faculty of Mechanical and Electrical Engineering, Polish Naval Academy, 81-127 Gdynia, Poland
Abstract
The underwater environment introduces many limitations that must be faced when designing an autonomous underwater vehicle (AUV). One of the most important issues is developing an effective vehicle movement control and mission planning system. This article presents a global trajectory planning system based on a multimodal approach. The trajectory of the vehicle’s movement has been divided into segments between introduced waypoints and calculated in parallel by advanced path planning methods: modified A* method, artificial potential field (APF), genetic algorithm (GA), particle swarm optimisation (PSO), and rapidly-exploring random tree (RRT). The shortest paths in each planned segment are selected and combined to give the resulting trajectory. A comparison of the results obtained by the proposed approach with the path calculated by each method individually confirms the increase in the system’s effectiveness by ensuring a shorter trajectory and improving the system’s reliability. Expressing the final trajectory in the form of geographical coordinates with a specific arrival time allows the implementation of calculation results in mission planning for autonomous underwater vehicles used commercially and in the military, as well as for autonomous surface vehicles (ASVs) equipped with trajectory tracking control systems.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference51 articles.
1. Kot, R., and Szymak, P. (2023, January 22–25). Fine-Tuning Method of the GA-based Collision Avoidance System for AUVs. Proceedings of the 2023 27th International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, Poland.
2. Cheng, C., Zhu, D., Sun, B., Chu, Z., Nie, J., and Zhang, S. (2015, January 3–6). Path planning for autonomous underwater vehicle based on artificial potential field and velocity synthesis. Proceedings of the 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE), Halifax, NS, Canada.
3. Solari, F.J., Rozenfeld, A.F., Villar, S.A., and Acosta, G.G. (2016, January 15–17). Artificial potential fields for the obstacles avoidance system of an AUV using a mechanical scanning sonar. Proceedings of the 2016 3rd IEEE/OES South American International Symposium on Oceanic Engineering (SAISOE), Buenos Aires, Argentina.
4. Williams, G.N., Lagace, G.E., and Woodfin, A. (1990, January 5–6). A collision avoidance controller for autonomous underwater vehicles. Proceedings of the Symposium on Autonomous Underwater Vehicle Technology, Washington, DC, USA.
5. A kinematic virtual potentials trajectory planner for AUV-s;IFAC Proc. Vol.,2007
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