A new framework solves the kidnapped robot problem by sampling sparse feasible hypotheses via constrained RRT and applying batched multi-stage inference with SMAD ordering and TAM alignment to achieve competitive success rate and efficiency on real robots.
Passive global localisation of mobile robot via 2D Fourier-Mellin invariant matching,
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Tackling the Kidnapped Robot Problem via Sparse Feasible Hypothesis Sampling and Reliable Batched Multi-Stage Inference
A new framework solves the kidnapped robot problem by sampling sparse feasible hypotheses via constrained RRT and applying batched multi-stage inference with SMAD ordering and TAM alignment to achieve competitive success rate and efficiency on real robots.