Reproduce “Continuous Occupancy Mapping in Dynamic Environments Using Particles” on OpenResearch
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About this paper
Gang Chen, Wei Dong, Peng Peng, Javier Alonso-Mora, Xiangyang Zhu
The authors present DSP-Dynamic, a continuous particle-based map of static and moving obstacles for planning. Weighted position-and-velocity particles are organized with Cartesian voxels and sensor-oriented pyramids for filtering and occlusion handling. Across three simulated worlds and three output resolutions, it averages best F1 0.46 and precision–recall AUC 0.47, versus K3DOM’s 0.33 and 0.37, but does not win every setting.
Summary by alphaXiv.
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