|Title||Application of grazing-inspired guidance laws to autonomous information gathering|
|Publication Type||Conference Proceedings|
|Year of Conference||2014|
|Authors||Apker, T, Liu, S-Y, Sofge, D, J. Hedrick, K|
|Conference Name||Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems|
|Conference Location||Chicago, IL|
Domestic grazing animals follow simple, scalable rules to assign themselves trajectories to cover a pasture. We explain how to adapt these rules for an information gathering system based on a realistic robot motion model and Kalmanfilter based evidence grid that accounts for both bandwidth and sensor limitations. Our results show that this algorithm can meet or exceed the performance of state of the art field robotics systems, particularly when scalability and robustness to failure are required.
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