Journal of the ACM (JACM)
Computer rendering of stochastic models
Communications of the ACM
Communications of the ACM
Tradeoffs Between Directed and Autonomous Driving on the Mars Exploration Rovers
International Journal of Robotics Research
Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots
International Journal of Robotics Research
Decisional autonomy of planetary rovers: Research Articles
Journal of Field Robotics
Extending the Path-Planning Horizon
International Journal of Robotics Research
Global planning on the Mars Exploration Rovers: Software integration and surface testing
Journal of Field Robotics - Special Issue on Space Robotics, Part II
Terrain Adaptive Navigation for planetary rovers
Journal of Field Robotics - Special Issue on Space Robotics, Part II
Differentially constrained mobile robot motion planning in state lattices
Journal of Field Robotics - Special Issue on Space Robotics, Part I
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Fast replanning for navigation in unknown terrain
IEEE Transactions on Robotics
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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.