AI RESEARCH
Goal inference with Rao-Blackwellized Particle Filters
arXiv CS.LG
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ArXi:2512.09269v2 Announce Type: replace Inferring the eventual goal of a mobile agent from noisy observations of its trajectory is a fundamental estimation problem. We initiate the study of such intent inference using a variant of a Rao-Blackwellized Particle Filter (RBPF), subject to the assumption that the agent's intent manifests through closed-loop behavior with a state-of-the-art provable practical stability property.