TY - GEN
T1 - Cloud computing based localization for mobile robot systems
AU - Li, Chung Ying
AU - Hsu, Chen Chien
AU - Wang, Wei Yen
AU - Chien, Yi Hsing
AU - Li, I. Hsum
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/4/28
Y1 - 2014/4/28
N2 - A robot localization plays an important role in the field of robot navigation. One of the most commonly used localization algorithms is Monte Carlo algorithm. To improve the efficiency of robot localization, many modified algorithms have been proposed, such as Self-Adaptive Monte Carlo algorithm. However, this method requires a lot of storage space and intensive computing, especially in large environments. In recent years, because of the rapid development of cloud computing, the data can be dynamically allocated. Therefore, this paper combines the Self-Adaptive Monte Carlo Localization algorithm with cloud computing. Some experimental results illustrate the proposed architecture, which can quickly establish the map database and provide the shared map information to multiple robots. In addition, the proposed method reduces the computational load and expands the scope of activities.
AB - A robot localization plays an important role in the field of robot navigation. One of the most commonly used localization algorithms is Monte Carlo algorithm. To improve the efficiency of robot localization, many modified algorithms have been proposed, such as Self-Adaptive Monte Carlo algorithm. However, this method requires a lot of storage space and intensive computing, especially in large environments. In recent years, because of the rapid development of cloud computing, the data can be dynamically allocated. Therefore, this paper combines the Self-Adaptive Monte Carlo Localization algorithm with cloud computing. Some experimental results illustrate the proposed architecture, which can quickly establish the map database and provide the shared map information to multiple robots. In addition, the proposed method reduces the computational load and expands the scope of activities.
KW - Cloud computing
KW - particle filter
KW - robot localization
KW - SAMCL
UR - http://www.scopus.com/inward/record.url?scp=84949928129&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84949928129&partnerID=8YFLogxK
U2 - 10.1109/CACS.2014.7097194
DO - 10.1109/CACS.2014.7097194
M3 - Conference contribution
AN - SCOPUS:84949928129
T3 - CACS 2014 - 2014 International Automatic Control Conference, Conference Digest
SP - 238
EP - 242
BT - CACS 2014 - 2014 International Automatic Control Conference, Conference Digest
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 International Automatic Control Conference, CACS 2014
Y2 - 26 November 2014 through 28 November 2014
ER -