Probabilistic Methods for State Estimation in Robotics

摘要: The eld of Arti cial Intelligence (AI) is currently undergoing a transition. While in the eighties, rule-based and logical representations were representation choice majority AI systems, recent years various researchers have explored alternative representational frameworks, which emphasis on frameworks that enable systems to represent handle uncertainty. Out those, probabilistic methods (and speci cally Bayesian methods) probably been analyzed most thoroughly applied successfully variety problem domains.