On-line estimation of power model parameters for skid-steer robots with applications in mission energy use prediction

This paper presents algorithms to predict the energy used by a skid-steer robot to complete a given path, including the refinement of that prediction during operation. The vast majority of commercially available ground mobile robots utilize skid-steer technology due to the robustness and maneuverability of the design. However, the complex track/terrain interactions developed during skid-steer maneuvers make traction-related power losses difficult to model. Accurate estimates of skid-steer power and energy usage enable more intelligent mission planning decisions to be made. In this study, a skid-steer power model that is linear in three unknown parameters was used and tested extensively on two skid-steer vehicles, one tracked and the other wheeled. Repeated testing shows good repeatability of estimated parameters, and results indicate that the tracked vehicle exhibits a much larger sensitivity to the surface types tested than the wheeled vehicle. The skid-steer power model is then combined with a kinematic model of skid-steer movement and a trajectory control algorithm to predict the energy required to complete a given traversal path. This is useful for estimating energy demands for retro-traversal, an application demonstrated in this study. The energy predictions are further refined through the mapping of power model parameters onto terrain types using overhead imagery of the area of operation. The maps are used to predict what terrain types will be encountered along the planned path to improve the estimate of the energy required.