[PaoPao Point Cloud Space-Time] Confidence-Rich Mutual Information for Information-Theoretic Mapping

A RAL 2021 paper proposes Confidence-Rich Mutual Information (CRMI), which computes information gain based on continuous probability distributions of occupancy grid cells and a beam sensor causal model (SCM), avoiding the shortcomings of the traditional inverse sensor model (ISM). Simulations and experiments show that CRMI-driven robots explore unexplored and ambiguous regions more finely, with quadratic complexity close to traditional OGMI, and can run online.