Analysis of hybridized MTSO-PID controller for path planning of autonomous underwater vehicle in obstacle-rich terrain

In Autonomous Underwater Vehicles, safe navigation planning brings new challenges due to the three-dimensional navigation and uncertainties of the underwater world. This study aims to develop an intelligent controller that can satisfy the aim of the study. To take advantage of the versatility of Tuna Swarm Optimization (TSO), where three different modes can be selected as per the requirements with some improvements such as adding an extra controlling parameter and hybridized with a PID controller and proposed Modified Tuna Swarm Optimization tuned PID controller (MTSO-PID). This proposed technique is implemented in the AUV and tested using simulation and experimental setup in a three-dimensional test environment to validate its effectiveness. MATLAB is used to construct the 3d underwater environment of size 4 × 15 × 4; all units are in meters. From the analysis of the simulation and experiment results, there was less than 7% deviation in travel time between simulation, and laboratory experiment was less than 6% deviation in path length. To determine the robustness of the proposed controller, the MTSO-PID controller is tested against different techniques such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bacteria Forge Optimization (BFO), and Whale Optimization Algorithms (WOA) in the same MATLAB environment. The comparison shows that the MTSO-PID controller takes an average of 8.21%, 18.55%, 10.49%, and 12.29% less path than PSO, ACO, WOA, and BFO algorithms. To further validate the ability of the proposed technique, it is compared with two previously developed techniques (AplusPF and improved A_star technique) which were used in AUV navigation. The comparison is drawn for three different test cases according to the initial heading angle of the AUV. Compared with the improved A_star method, significant reductions in path length by 29.29%, 13.62%, and 15.22% are noticed for 0°, 45°, and 90° initial heading angle conditions.