By Topic

Mobile vehicle navigation in unknown environments: a multiple hypothesis approach

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
D. Maksarov ; Dept. of Eng. Sci., Oxford Univ., UK ; H. Durrant-Whyte

The paper describes an algorithm for sensor-based map building and navigation for an autonomous mobile vehicle. The algorithm is based on the use of an extended Kalman filter to obtain estimates of the location and identity of geometric features in an unknown environment. A multitarget tracking methodology is applied to the evaluation of multiple hypotheses about the locations of geometric features in the environment. The algorithm does not require any a priori information about the environment. It is capable of initiating new geometric features and identifying the type of a geometric feature from the given set of geometric features, utilising the data provided by a set of sonar sensors. The algorithm is also capable of deleting geometric features from the map of the environment when they are no longer detected by the sensors. The implementation of the algorithm is discussed, and results using real sonar data are presented

Published in:

IEE Proceedings - Control Theory and Applications  (Volume:142 ,  Issue: 4 )