Abstract
Computationally efficient SLAM (CESLAM) has been proposed to solve simultaneous localization and mapping problem in real-time design. CESLAM first uses the landmark measurement with the maximum likelihood to update the particle states and then update their associated landmarks later. This improves the accuracy of localization and mapping by avoiding unnecessary comparisons. This paper describes a modified version of CESLAM called rapidly operations SLAM (ROSLAM) which improves the runtime even further. We present an empirical evaluation of ROSLAM in a simulated environment which shows that it speeds up previous well known algorithms by 100 %.
Original language | English |
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Title of host publication | Robot Intelligence Technology and Applications 4 - Results from the 4th International Conference on Robot Intelligence Technology and Applications |
Editors | Fakhri Karray, Jong-Hwan Kim, Hyun Myung, Jun Jo, Peter Sincak |
Publisher | Springer Verlag |
Pages | 65-74 |
Number of pages | 10 |
ISBN (Print) | 9783319312910 |
DOIs | |
Publication status | Published - 2017 Jan 1 |
Event | 4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015 - Bucheon, Korea, Republic of Duration: 2015 Dec 14 → 2015 Dec 16 |
Publication series
Name | Advances in Intelligent Systems and Computing |
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Volume | 447 |
ISSN (Print) | 2194-5357 |
Other
Other | 4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015 |
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Country | Korea, Republic of |
City | Bucheon |
Period | 15/12/14 → 15/12/16 |
Fingerprint
Keywords
- CESLAM
- Extended kalman filter
- FastSLAM
- Particle filter
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science(all)
Cite this
ROSLAM-A faster algorithm for simultaneous localization and mapping (SLAM). / Huang, Teng Wei; Hsu, Chen-Chien James; Wang, Wei-Yen; Baltes, Hansjoerg (Jacky).
Robot Intelligence Technology and Applications 4 - Results from the 4th International Conference on Robot Intelligence Technology and Applications. ed. / Fakhri Karray; Jong-Hwan Kim; Hyun Myung; Jun Jo; Peter Sincak. Springer Verlag, 2017. p. 65-74 (Advances in Intelligent Systems and Computing; Vol. 447).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - ROSLAM-A faster algorithm for simultaneous localization and mapping (SLAM)
AU - Huang, Teng Wei
AU - Hsu, Chen-Chien James
AU - Wang, Wei-Yen
AU - Baltes, Hansjoerg (Jacky)
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Computationally efficient SLAM (CESLAM) has been proposed to solve simultaneous localization and mapping problem in real-time design. CESLAM first uses the landmark measurement with the maximum likelihood to update the particle states and then update their associated landmarks later. This improves the accuracy of localization and mapping by avoiding unnecessary comparisons. This paper describes a modified version of CESLAM called rapidly operations SLAM (ROSLAM) which improves the runtime even further. We present an empirical evaluation of ROSLAM in a simulated environment which shows that it speeds up previous well known algorithms by 100 %.
AB - Computationally efficient SLAM (CESLAM) has been proposed to solve simultaneous localization and mapping problem in real-time design. CESLAM first uses the landmark measurement with the maximum likelihood to update the particle states and then update their associated landmarks later. This improves the accuracy of localization and mapping by avoiding unnecessary comparisons. This paper describes a modified version of CESLAM called rapidly operations SLAM (ROSLAM) which improves the runtime even further. We present an empirical evaluation of ROSLAM in a simulated environment which shows that it speeds up previous well known algorithms by 100 %.
KW - CESLAM
KW - Extended kalman filter
KW - FastSLAM
KW - Particle filter
UR - http://www.scopus.com/inward/record.url?scp=84988273213&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84988273213&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-31293-4_6
DO - 10.1007/978-3-319-31293-4_6
M3 - Conference contribution
AN - SCOPUS:84988273213
SN - 9783319312910
T3 - Advances in Intelligent Systems and Computing
SP - 65
EP - 74
BT - Robot Intelligence Technology and Applications 4 - Results from the 4th International Conference on Robot Intelligence Technology and Applications
A2 - Karray, Fakhri
A2 - Kim, Jong-Hwan
A2 - Myung, Hyun
A2 - Jo, Jun
A2 - Sincak, Peter
PB - Springer Verlag
ER -