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Abstract: A map is an abstract internal representation of an environment for a mobile robot, and how to learn it autonomously is one of the most fundamental issues in the research fields of intelligent robotics and artificial intelligence. In this paper, we propose a topological map learning method for mobile robots which constructs a POMDP-based discrete state transition model from time-series data of observations and actions. The main point of this method is to find a set of states or nodes of... (Update)
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BibTeX entry: (Update)
@misc{ yairi-learning,
author = "Takehisa Yairi and Masahito Togami and Koichi Hori",
title = "Learning Topological Maps from Sequential Observation and Action Data under
Partially Observable Environment",
url = "citeseer.ist.psu.edu/550193.html" }
Citations (may not include all citations):211 A robot exploration and mapping strategy based on a semantic.. - Kuipers, Byun - 1991
206 High resolution maps from wide angle sonar (context) - Moravec, Elfes - 1985
158 Integration of representation into goal-driven behavior-base.. (context) - Mataric - 1992
79 Topological mapping for mobile robots using a combination of.. (context) - Kortenkamp, Weymouth - 1994
77 Learning topological maps with weak local odometric informat.. - Shatkay, Kaelbling - 1997
36 Integrating topological and metric maps for mobile robot nav.. - Thrun, Gutmann et al. - 1998
34 An information-theoretic analysis of hard and soft assignmen.. - Kearns, Mansour et al. - 1997
32 Learning to explore and build maps - Pierce, Kuipers - 1994
4 cient estimation of the number of clusters (context) - Pelleg, Moore et al. - 2000
4 Concurrent localization and map building for mobile robots u.. (context) - Rencken - 1993
2 Estimating markov model structures - Brants - 1996
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Fast and Simple Topological Map Construction Based on.. - Yairi, Hirama, Hori (2001) (Correct)
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