Research Information System
IEEE 20th International Conference on Automation Science and Engineering (CASE), Bari, Italy, 28 August - 01 September 2024, pp.3773-3778, (Full Text)
In this paper, a new, robust, and computationally feasible motion planning algorithm is introduced to solve the path planning, navigation, and probabilistic coverage problems related to the Unmanned Underwater Vehicles (UUV). The approach given in this paper is based on feedback motion planning with random sequential composition (RSC) method. Initially, the RSC method was capable of 2D motion planning with a sparse tree structure. In this work, the sparsity of the RSC method is enhanced using an approach called "circular enlarged funnels," and the algorithm is extended for 3D path planning of UUVs. Then, the proposed method is tested on MATLAB software in a 2D environment with the kinematic model of the UUV. After that, the 3D extension is tested with the realistic dynamical model of the UUV built on ROS/Gazebo environment, with and without environmental disturbances, to show the robustness of the resulting feedback policies. The results of these simulations showed that the proposed method can solve the path planning problem of UUVs in a robust and computationally feasible way with enhanced sparsity.