Energy efficient path planning for skid-steered autonomous ground vehicles

It is important to minimize the energy consumption of autonomous ground vehicles (AGVs) deployed in real world missions. One of the ways that this can be accomplished is to choose the vehicle's motion to minimize the mechanical and electrical energy usage required by the vehicle's motion. This paper considers energy efficient motion planning for skid-steered AGVs, an important and large class of all-terrain vehicles. An experimentally verified power consumption model for skid-steered vehicles has been recently developed based on the "exponential friction model," which yields power consumption predictions that are far more accurate than those obtained using Coulomb's friction model. At a given velocity the power consumption is essentially a function of the vehicle turning radius. This paper demonstrates energy efficient motion planning using Sampling Based Model Predictive Optimization (SBMPO), a recently developed motion planning algorithm. In this research SBMPO uses a simple kinematic model of the vehicle to determine feasible vehicle paths and the skid-steered vehicle power model to compute the energy consumption (i.e., the cost) along a given trajectory. The results here are for a vehicle moving on a single surface at constant velocity. Energy optimal motion planning is compared with distance optimal motion planning and the results demonstrate the importance of considering energy consumption in the motion planning process.