Title :
Finding landmarks for mobile robot navigation
Author :
Thrun, Sebastian
Author_Institution :
Dept. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
Localization addresses the problem of determining the position of a mobile robot from sensor data. This paper presents an algorithm, called BaLL, which enables a mobile robot to learn a set of landmarks used in localization and to learn how to recognize them using artificial neural networks. BaLL is based on a statistical localization approach. It is applicable to a large variety of sensors and environments. Experiments with a mobile robot equipped with sonar sensors and a camera illustrate that BaLL identifies highly useful landmarks
Keywords :
Bayes methods; Kalman filters; Markov processes; learning (artificial intelligence); mobile robots; neural nets; path planning; sonar; BaLL algorithm; mobile robot navigation; sonar sensors; statistical localization approach; Artificial neural networks; Books; Computer science; Humans; Large-scale systems; Mobile robots; Navigation; Robot kinematics; Robot sensing systems; Sonar;
Conference_Titel :
Robotics and Automation, 1998. Proceedings. 1998 IEEE International Conference on
Conference_Location :
Leuven
Print_ISBN :
0-7803-4300-X
DOI :
10.1109/ROBOT.1998.677210
