Path planning with variable-fidelity terrain assessment

Terrain assessment and path planning for mobile robots are intrinsically linked. There exists 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 the available sensor data, the visible terrain is first 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. This can be thought of as providing a means to triage large amounts of terrain data. 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 a system using one implementation of the technique on a large number of simulated path planning problems in fractal terrain. Additionally, we provide results and system details from an experimental field test carried out on Devon Island, Canada.

► A path planner that considers the cost of terrain assessment at the planning stage.
► An investigation into the true cost of using high-fidelity terrain assessment.
► Simulation results showing the influence of the cost of high-fidelity assessment.
► A proof-of-concept system on a field robot deployed in the Canadian High Arctic.