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Persistent Homology for Post-Processing Occupancy Grid Maps

Explore the application of persistent homology for refining occupancy grid maps by thresholding scalar fields at varying levels. Learn about superlevels, simplicial complexes, and optimal thresholds for optimizing grid map accuracy. See a simulation example with unbounded localization noise.

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Persistent Homology for Post-Processing Occupancy Grid Maps

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  1. POST PROCESSING OF OCCUPANCY GRID MAPS USING PERSISTENT HOMOLOGY Ragesh Kumar Ramachandran and Spring Berman Robotic Embedded Systems Laboratory Autonomous collective systems Laboratory

  2. Motivation

  3. Basic idea • Scalar field associated with occupancy grid maps. • The scalar  field is thresholded at various levels. • The superlevel associated with each level.

  4. Persistent Homology Simplicial complex Cubical complex

  5. Methodology

  6. Simulation Example Optimal threshold Barcode Unoccupancy map Environment Unoccupancy grid map from simulation data with unbounded localization noise

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