Path planning with variable-fidelity terrain assessment

Terrain assessment and path planning are intrinsically linked. There exist a variety of terrain-assessment algorithms and these methods follow the trend of low-fidelity at low-cost and high-fidelity at high-cost. We present a modular path-planning algorithm that uses a hierarchy of terrain-assessment methods; from low-fidelity to high-fidelity. Using all the available sensor data, the visible terrain is assessed with the low-fidelity, low-cost method. The decision to assess a piece of terrain with the high-fidelity, high-cost method is made considering potential path benefits and the cost of assessment. The result is a lower combined cost of the path and terrain assessment that exploits the capabilities of the robot chassis where prudent. We demonstrate the technique on a large number of simulated path-planning problems using fractal terrain, as well as provide preliminary results from an experimental field test carried out on Devon Island, Canada.