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GPU-Accelerated Incremental Euclidean Distance Transform for Online Motion Planning of Mobile Robots

This paper proposes a voxel mapping system that uses parallel computing to simultaneously generate occupancy grid maps (OGMs) and Euclidean distance transforms (EDTs), and incrementally builds a global EDT to output high-frequency local distance information for online motion planning. The system uses GPU programming to compute EDT in parallel within local volumes, then continuously integrates new observations into the global EDT via a parallel wavefront algorithm while preserving historical observations.

Part of the event: GPU-Accelerated Incremental Euclidean Distance Transform for Online Motion Planning

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