Experimental Results for Spline Based Obstacle Avoidance of an Off-Road Ground Vehicle

For point to point navigation, calculating suitable paths for an an autonomous ground vehicle is computationally difficult. Maneuvering an autonomous vehicle safely around obstacles is essential, and the ability to generate safe paths in a real time environment is crucial for vehicle viability. We previously presented a method for developing feasible paths through complicated environments using a baseline smooth path based on cubic splines. This method iteratively refines the path to more directly compute a feasible path and thus find an efficient, collision free path in real time through an unstructured environment. This method, when implemented in a receding horizon fashion, becomes the basis for high level control. Previous work on spline collision free path generation is extended to include experimental validation using the Overbot, an autonomous ground vehicle developed for the original DARPA Grand Challenge in 2004. Using the previously developed software, an information grid is populated with potential obstacles. This grid becomes the basis for the pixel search along the spline path, that identifies collision points to be resolved with the presented methodology. Tests are conducted on a 600m offroad course using randomly generated virtual obstacles. Experimental results demonstrate good performance, with collision free paths being found, or a termination criteria reached, in under one second.