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RPT*: Global Planning with Probabilistic Terminals for Target Search in Complex Environments

The paper studies the Hamiltonian Path Problem with Probabilistic Terminals (HPP-PT), whose goal is for a mobile robot to visit all candidate locations to find a target while minimizing expected path cost. The authors propose RPT*, a search method with optimality guarantees that uses dynamic programming in a new state space to bypass history dependency, along with a heuristic to speed up computation. The RPT*-based HATS system, combined with Bayesian filtering or autonomous exploration, found targets faster than baseline methods on average in both simulation and real-robot experiments.

Part of the event: RPT* and HATS: Target Search Planning with Probabilistic Endpoints

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