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Path finding is a fundamental, yet computationally expensive problem in robotics navigation. Often times, it is necessary to sacrifice optimality to find a feasible plan given a time constraint due to the search complexity. Dynamic environments may further invalidate current computed plans, requiring an efficient planning strategy that can repair existing solutions. This paper presents a massively parallelizable wavefront-based approach to path planning, running on the GPU, that can efficientlydoi:10.1109/iros.2013.6696830 dblp:conf/iros/KapadiaGBB13 fatcat:2vphidkd4rbyvnqnzesssvmz4y