Real-time Model Based Path Planning for Wheeled Vehicles

This work presents a model based traversability analysis method which employs a detailed vehicle model to perform real-time path planning in complex environments. The vehicle model represents the vehicle’s wheels and chassis, allowing it to accurately predict the vehicles 3D pose, detailed contact information for each wheel and the occurrence of a chassis collision given a 2D pose on an elevation map. These predictions are weighted, depending on the safety requirements of the vehicle, to provide a scoring function for an A*-like search strategy. The proposed method is designed to run at frame rates of 30Hz on data from a RGB-D sensor to provide reactive planning of safe paths. For evaluation, two wheeled mobile robots in different simulated and real world environment setups were tested to show the reliability and performance of the proposed method.