Path planning for an unmanned terrestrial vehicle in an obstacle ridden environment
Thesis (MEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009.
This thesis relates to the successful development of an unmanned terrestrial vehicle (UTV) capable of operating in an obstacle ridden environment. The primary focus of the project is on the specific path planning algorithms. It is shown that specific methods of populating the obstacle-free space can be combined with methods of extracting the shortest path from these popula- tions. Through use of such combinations the successful generation of optimal collision-free paths is demonstrated. Previously developed modular architectures are combined and modified to create a UTV platform which meets all the requirements for implementation of navigational systems and path planning algorithms on board the platform. A two-dimensional kinematic state estimator is developed. This estimator makes use of extended Kalman Filter theory to optimally combine measurements from low cost sensors to yield the vehicle’s state vector. Lateral guidance controllers are developed to utilize this estimated state vector in a feedback control configuration. The entire system is then successfully demonstrated within a simulation environment. Finally, practical results from two days of test runs are provided in both written and interactive form