Probabilistic modeling and analysis of high-speed rough-terrain mobile robots

Mobile robots have important applications in high speed, rough-terrain scenarios. It would be desirable to construct accurate models of these systems. However, due to the system complexity, accurate modeling is difficult. In This work a high-speed rough-terrain robot model is presented. Experiments show that this model can accurately predict robot performance in simple, well-known terrain. However in unstructured, rough terrain, performance prediction is less accurate. A stochastic method for analyzing system performance in spite of model parameter uncertainty is presented. A method for studying model sensitivity to parameter uncertainty is also presented. It is shown that stochastic analysis can be used effectively for model-based analysis of real-world rough-terrain robotic systems.