Abstract
This paper proposes a method of global localization on a map with large uncertainty. Since the pose of a mobile robot represented in a global frame of reference might be inconsistent on an inaccurate map, the method represents the robot pose in a local frame attached to a landmark. When the robot finds a new landmark, the robot transforms as pose from the old landmark frame to the new one based on the relative pose between the landmarks. Map errors are represented by probability density functions defined on these relative poses. The paper presents an extension of Markov localization which is augmented so as to incorporate the map errors into data fusion process, and shows experimental results.
| Original language | English |
|---|---|
| Title of host publication | IEEE International Conference on Intelligent Robots and Systems |
| Pages | 399-404 |
| Number of pages | 6 |
| Volume | 1 |
| Publication status | Published - 2001 |
| Externally published | Yes |
| Event | 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems - Maui, HI Duration: 2001 Oct 29 → 2001 Nov 3 |
Other
| Other | 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems |
|---|---|
| City | Maui, HI |
| Period | 01/10/29 → 01/11/3 |
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ASJC Scopus subject areas
- Control and Systems Engineering
Cite this
Mobile robot localization based on an inaccurate map. / Tomono, Masahiro; Yuta, Shinichi.
IEEE International Conference on Intelligent Robots and Systems. Vol. 1 2001. p. 399-404.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Mobile robot localization based on an inaccurate map
AU - Tomono, Masahiro
AU - Yuta, Shinichi
PY - 2001
Y1 - 2001
N2 - This paper proposes a method of global localization on a map with large uncertainty. Since the pose of a mobile robot represented in a global frame of reference might be inconsistent on an inaccurate map, the method represents the robot pose in a local frame attached to a landmark. When the robot finds a new landmark, the robot transforms as pose from the old landmark frame to the new one based on the relative pose between the landmarks. Map errors are represented by probability density functions defined on these relative poses. The paper presents an extension of Markov localization which is augmented so as to incorporate the map errors into data fusion process, and shows experimental results.
AB - This paper proposes a method of global localization on a map with large uncertainty. Since the pose of a mobile robot represented in a global frame of reference might be inconsistent on an inaccurate map, the method represents the robot pose in a local frame attached to a landmark. When the robot finds a new landmark, the robot transforms as pose from the old landmark frame to the new one based on the relative pose between the landmarks. Map errors are represented by probability density functions defined on these relative poses. The paper presents an extension of Markov localization which is augmented so as to incorporate the map errors into data fusion process, and shows experimental results.
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UR - http://www.scopus.com/inward/citedby.url?scp=0035559776&partnerID=8YFLogxK
M3 - Conference contribution
VL - 1
SP - 399
EP - 404
BT - IEEE International Conference on Intelligent Robots and Systems
ER -