Reproduce “Robot localization in a mapped environment using Adaptive Monte Carlo algorithm” on OpenResearch
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About this paper
Sagarnil Das
The paper demonstrates AMCL-based localization and navigation for two simulated robots in a known maze. AMCL maintains candidate poses, updates them with odometry and laser readings, and resamples those that better match the map. UdacityBot and SagarBot reached the goal, but took suboptimal routes; convergence times were 5–6 and 30–40 seconds, respectively. The simulation does not establish optimal planning or hardware readiness.
Summary by alphaXiv.
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