Motion-based Identification of Multiple Mobile Robots using Trajectory Analysis in a Well-configured Environment with Distributed Vision Sensors
- Authors
- Kim, Joo-Hyung; Lee, Jeong-Eom; Lee, Joo-Ho; Park, Gwi-Tae
- Issue Date
- 8월-2012
- Publisher
- INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS
- Keywords
- Distributed vision sensors; motion-based robot identification; multiple mobile robots; well-configured environment
- Citation
- INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, v.10, no.4, pp.787 - 796
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
- Volume
- 10
- Number
- 4
- Start Page
- 787
- End Page
- 796
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/107781
- DOI
- 10.1007/s12555-012-0415-4
- ISSN
- 1598-6446
- Abstract
- Networked mobile robots are able to determine their poses (i.e., position and orientation) with the help of a well-configured environment with distributed sensors. Before localizing the mobile robots using distributed sensors, the environment has to have information on each of the robots' prior knowledge. Consequently, if the environment does not have information on the prior knowledge of a certain mobile robot then it will not determine its current pose. To solve this restriction, as a preprocessing step for indoor localization, we propose a motion-based identification of multiple mobile robots using trajectory analysis. The proposed system identifies the robots by establishing the relation between their identities and their positions, which are estimated from their trajectories related to each of the paths generated as designated signs. The primary feature of the proposed system is the fact that networked mobile robots are quickly and simultaneously able to determine their poses in well-configured environments. Experimental results show that our proposed system simultaneously identifies multiple mobile robots, and approximately estimates each of their poses as an initial state for autonomous localization.
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Collections - College of Engineering > School of Electrical Engineering > 1. Journal Articles
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