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Distributed environment representation and object localization system in intelligent space

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Abstract

A kind of new environment representation and object localization scheme is proposed in the paper aiming to accomplish the task of object operation more efficiently in intelligent space. First, a distributed environment representation method is put forward to reduce storage burden and improve the system’s stability. The layered topological maps are separately stored in different landmarks attached to the key positions of intelligent space, so that the robot can search the landmarks on which the map information can be read from the QR code, and then the environment map can be built autonomously. Map building is an important prerequisite for object search. An object search scheme based on RFID and vision technology is proposed. The RFID tags are attached to the target objects and reference objects in the indoor environment. A fixed RFID system is built to monitor the rough position (room and local area) of target and a mobile RFID system is constructed to detect the targets which are not in the covering range of the fixed system. The existing area of target is determined by the time sequence of reference tags and target tags, and the accurate position is obtained by onboard vision system at a short distance. The experiments demonstrate that the distributed environment representation proposed in the paper can fully meet the requirements of object localization, and the positioning scheme has high search efficiency, high localization accuracy and precision, and a strong anti-interference ability in the complex indoor environment.

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Authors and Affiliations

  1. School of Control Science and Engineering, Shandong University, Jinan Shandong, 250061, China

    Yinghua Xue, Guohui Tian, Baoye Song & Taotao Zhang

  2. School of Computer and Information Engineering, Shandong University of Finance, Jinan Shandong, 250014, China

    Yinghua Xue

Authors
  1. Yinghua Xue
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  2. Guohui Tian
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  3. Baoye Song
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  4. Taotao Zhang
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Corresponding author

Correspondence to Yinghua Xue.

Additional information

This work was supported by the National High Technology Research and Development Program of China (No. 2009AA04Z220), and the National Natural Science Foundation of China (No. 61075092).

Yinghua XUE is a lecturer in Shandong University of Finance and is currently pursuing Ph.D. degree in School of Control Science and Engineering of Shandong University. She obtained her B.S. degree from Shanghai Jiaotong University in 1996, and M.S. degree from Shandong University in 2000. Her research interests include intelligent space, multipattern information acquisition, object localization and operation.

Guohui TIAN was born in August 1969 in Hebei, China. He is a professor and the deputy dean in School of Control Science and Engineering, Shandong University. And also he is the member of Chinese Association for Artificial Intelligence and International Association for Intelligent Autonomous System. He received the B.S. degree from Department of Mathematics, Shandong University, Jinan, China, in 1990, the M.S. degree from the Department of Automation, Shandong University of Technology, Jinan, China, in 1993, and the Ph.D. degree from School of Automation, Northeastern University, Shenyang, China, in 1997. He studied as a post-Doctorial researcher in School of Mechanical Engineering of Shandong University from 1999 to 2001, and studied as a visiting professor in Graduate School of Engineering of Tokyo University of Japan from 2003 to 2005. His research interests include service robot, intelligent space, collaboration and cooperation of multi-robot system.

Baoye SONG was born in Qingdao, China, in 1982. He is currently pursuing Ph.D. degree in School of Control Science and Engineering of Shandong University. He received his B.S and M.S degree in Automation and Control Science and Engineering from Qingdao University of Science and Technology, in 2005 and 2008, respectively. His research interests include sensor networks, sensor fusion and mobile robot control. He is a student member of IEEE.

Taotao ZHANG was born in Weifang, China, in 1986. He is currently pursuing M.S. degree in School of Control Science and Engineering of Shandong University. He received his B.S degree in Automation from Hunan University, in 2008. His research interests include robot map building and robot navigation. He is a student member of IEEE.

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Xue, Y., Tian, G., Song, B. et al. Distributed environment representation and object localization system in intelligent space. J. Control Theory Appl. 10, 371–379 (2012). https://doi.org/10.1007/s11768-012-0172-1

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  • DOI: https://doi.org/10.1007/s11768-012-0172-1

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