TY - GEN
T1 - Improvement of outdoor localization based on particle filter through video information's variable uncertainty
AU - Kim, Dong
AU - Song, Jae Bok
AU - Choi, Ji Hoon
PY - 2012
Y1 - 2012
N2 - Localization of a mobile robot is a very important issue for robot's navigation. However, localization method with conventional wheel odometry has limits in case the wheel faces slippery conditions. As an alternative way, visual odometry has been researched continuously. However, this method alone has also difficulty for robust localization because wrong depth measurement can frequently occur and the error is accumulated continuously. Even though localization can be improved by using particle filter, this method is dependent on the accuracy of the reference map. For improving these drawbacks, this research utilized variable uncertainty useful for denoting accuracy of motion model from video information. Consequently, localization in the environments represented by inaccurate maps was improved compared to the conventional method.
AB - Localization of a mobile robot is a very important issue for robot's navigation. However, localization method with conventional wheel odometry has limits in case the wheel faces slippery conditions. As an alternative way, visual odometry has been researched continuously. However, this method alone has also difficulty for robust localization because wrong depth measurement can frequently occur and the error is accumulated continuously. Even though localization can be improved by using particle filter, this method is dependent on the accuracy of the reference map. For improving these drawbacks, this research utilized variable uncertainty useful for denoting accuracy of motion model from video information. Consequently, localization in the environments represented by inaccurate maps was improved compared to the conventional method.
KW - Monte Carlo Localization(MCL)
KW - Particle filter
KW - Visual odometry
UR - http://www.scopus.com/inward/record.url?scp=84874693560&partnerID=8YFLogxK
U2 - 10.1109/URAI.2012.6462958
DO - 10.1109/URAI.2012.6462958
M3 - Conference contribution
AN - SCOPUS:84874693560
SN - 9781467331104
T3 - 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2012
SP - 163
EP - 166
BT - 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2012
T2 - 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2012
Y2 - 26 November 2012 through 29 November 2012
ER -