Probabilistic Robot Navigation in Partially Observable Environments

Reid G. Simmons, Sven Koenig
1995 International Joint Conference on Artificial Intelligence  
Autonomous mobile robots need very reliable navigation capabilities in order to operate unattended for long periods of time This paper reports on first results of a research program that uses par tially observable Markov models to robustly track a robot s location in office environments and to direct its goaJ-onented actions The approach explicitly maintains a probability distribution over the possi ble locations of the robot taking into account var IOUS sources of uncertainly including
more » ... ate knowledge of the environment and actuator and sensor uncertainty A novel feature of our approach is its integration of topological map information with approximate metric information We demon stcate Itw robustness of this appiorch «\ controlling an actuaJ indoor mobile robot navigating corridors 1 10B0 LEARNING
dblp:conf/ijcai/SimmonsK95 fatcat:zbsq54g7nbdmljfbz4e6ewlqzm