Mobility Planning for Autonomous Navigation of Multiple Robots in Unstructured Environments

Abstract

We describe an approach to mobility planning for autonomous navigation of multiple vehicles in unstructured environments. At the lowest level, this approach uses command arbitration in order to combine command recommendation from driving behaviors. Driving behaviors include local behaviors such as obstacle avoidance or goal tracking, and strategic behavior such as route planning to distant goals. Obstacle avoidance is performed by evaluating a fixed command set with respect to a terrain map built from 3D sensors. Route planning is based on the D* dynamic route planner which evaluates the command set based on the currently optimal path to the next goal. An additional planner, called GRAMMPS, is used to continuously analyze the outputs of the route planners running on each of the vehicles and re-computes optimally the allocation of goals to vehicles in order to minimize time and distance travelled. This approach has be exercised extensively with two vehicles using stereo and LADAR for obstacle detection and map building.