In this thesis, a path planning method using a three-level hierarchical system model is proposed. In the top level of the hierarchy, the given location points to visit are taken as waypoints. The waypoint navigation process is formulated as a traveling salesman problem (TSP). The Lin-Kernighan algorithm is used to solve the TSP and transfer the solution to the lower level of the hierarchy. In the middle level, the path is represented by a grid-based costmap. A novel modified Grossberg neural network is designed to solve the point-to-point path planning. The bottom level of the hierarchy smoothens the path with kinematic constraints. The final results are simulated in a 3D virtual reality environment by using the MATLAB VR toolbox --Abstract, page iii
