Simultaneous Planning and Control for Autonomous Ground Vehicles

Abstract

Motion planning and control for autonomous vehicles are complex tasks that must be done in order for a ground robot to operate in a cluttered environment. This dissertation presents the theory, implementation, and test results for some new and novel Receding Horizon Control (RHC) techniques that allow these tasks to be unified into one. The first new method is called Heuristic Receding Horizon Control (HRHC), and uses a modified A* search to fulfill the online optimization required by RHC. The second is called Dual-Frequency Receding Horizon Control (DFRHC), and is used to simplify the trajectory planning process during the RHC optimization. Both methods are combined together to form a practical implementation, which is discussed in detail. The autonomous ground vehicle, the NaviGator, developed at the Center for Intelligent Machines and Robotics, serves as a platform for the implementation and testing discussed.