A tableau method for reactive path planning in an obstacle avoidance system

Autonomous off-road vehicles face the daunting challenge of successfully navigating through terrain in which unmapped obstacles present hazards to safe vehicle operation. These obstacles can be sparsely scattered or densely clustered. The obstacle avoidance (OA) system on-board the autonomous vehicle must be capable of detecting all non-negotiable obstacles and planning paths around them in a sufficient computing interval to permit effective operation of the platform. To date, the reactive path planning function performed by OA systems has been essentially an exhaustive search through a set of preprogrammed swaths (linear trajectories projected through the on-board local obstacle map) to determine the best path for the vehicle to travel toward achieving a goal state. Historically, this function is a large consumer of computational resources in an OA system. A novel reactive path planner is described that minimizes processing time through the use of pre-computed indices into an n over n+1 tableau structure with the lowest level in the tableau representing the traditional "histogram" result. The tableau method differs significantly from other reactive planners in three ways: 1) the entire tableau is computed off-line and loaded on system startup, minimizing computational load; 2) the real-time computational load is directly proportional to the number of grid points searched and proportional to the square of the number of paths; and 3) the tableau is independent of grid resolution. Analytical and experimental comparisons of the tableau and histogram methods are presented along with generalization into an autonomous mobility system incorporating multiple feature planes and path cost evaluation.