Tracking and localization for omni-directional mobile industrial robot using reflectors

doi:10.1007/s40436-018-0216-y

Advances in Manufacturing ›› 2018, Vol. 6 ›› Issue (1): 118-125.doi: 10.1007/s40436-018-0216-y

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Tracking and localization for omni-directional mobile industrial robot using reflectors

Shuai Guo¹, Ting-Ting Fang¹, Tao Song¹, Feng-Feng Xi², Bang-Guo Wei¹

1 Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200444, People's Republic of China;
2 Department of Aerospace Engineering, Ryerson University, Toronto, Canada

Received:2017-04-17 Revised:2018-01-24 Online:2018-03-25 Published:2018-03-25
Contact: Tao Song,songtao43467226@shu.edu.cn E-mail:songtao43467226@shu.edu.cn
Supported by:
This work was supported by the Shanghai Municipal Science and Technology Commission (Grant No. 15550721900).

Abstract

Abstract:

In this paper, an improved tracking and localization algorithm of an omni-directional mobile industrial robot is proposed to meet the high positional accuracy requirement, improve the robot's repeatability positioning precision in the traditional trilateral algorithm, and solve the problem of pose lost in the moving process. Laser sensors are used to identify the reflectors, and by associating the reflectors identified at a particular time with the reflectors at a previous time, an optimal triangular positioning method is applied to realize the positioning and tracking of the robot. The experimental results show that positioning accuracy can be satisfied, and the repeatability and anti-jamming ability of the omni-directional mobile industrial robot will be greatly improved via this algorithm.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-018-0216-y

Key words: Mobile industrial robot, Tracking and positioning, Matching

Shuai Guo, Ting-Ting Fang, Tao Song, Feng-Feng Xi, Bang-Guo Wei. Tracking and localization for omni-directional mobile industrial robot using reflectors[J]. Advances in Manufacturing, 2018, 6(1): 118-125.

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References

1. Montemerlo M, Thrun S, Koller D (2002) A factored solution to the simultaneous localization and mapping problem. Eighteenth Natl Conf Artif Intell 50(2):593-598
2. Lei L (2002) Present state and future development of mobile robot technology research. Robot 24(5):475-480
3. Larsson U, Forsberg J, Wernersson A (1996) Mobile robot localization:integrating measurements from a time-of-flight laser. IEEE Trans Ind Electron 43(3):422-431
4. Buschka P, Saffiotti A, Wasik Z (2000) Fuzzy landmark-based localization for a legged robot. In:proceedings of the 2000 IEEE/RSJ Int Conf Intell Robot Syst 2:1205-1210
5. Jang G, Lee S, Kweon I (2002) Color landmark based self-localization for indoor mobile robots. In:proceedings of the 2002 IEEE international conference on robotics & automation 1037-1042
6. Madsen CB, Andersen CS (1998) Optimal reflector selection for triangulation of robot position. Robot Auton Syst 23(4):277-292
7. Betke M, Gurvits L (1997) Mobile localization using landmarks. IEEE Trans Robot Autom 13(2):251-263
8. Kai OA, Tomatis N, Jensen BT et al (2001) Multisensor on-thefly localization:precision and reliability for applications. Robot Auton Syst 34(2-3):131-143
9. Liu YM (2003) Three-dimensional optical positioning method research. Dissertation, Shenyang University of Technology
10. Zhang XD, Niu JX, Dong ZL (2002) Localization algorithm of autonomous mobile robot based on measuring angle. J Northeastern Univ 23(12):1143-1146
11. Sheng Y (2007) Study on vehicle mounted control system. Dissertation, Hefei University of Technology
12. Lei B, Liu BF, Liu DZ et al (2013) Research of AGV localization optimization based on landmark. Transducer Microsyst Technol 125(3):4516-4519
13. Liu Y (2007) Discussion on laser positioning algorithm of laser guidance AGV. Logist Mater Handl 12(11):100-101
14. Yu YB (2006) Research on sensor network location algorithm and related technology. Dissertation, Chongqing University
15. Jia W, Zhou W, Kaiser J (2001) Efficient algorithm for mobile multicast using anycast group. IEEE Procee-Commun 148(1):14-18
16. Mendes A, Nunes U (2004) Situation-based multi-target detection and tracking with laser-scanner in outdoor semi-structured environment. IEEE/RSJ Int Conf Intell Robot Syst 1(1):88-93
17. Wu SX, Yang M (2007) Reflector pair based localization for intelligent vehicles using laser radar. In:proceedings of the 2007 IEEE intelligent vehicles symposium 209-214
18. Yang M, Wang C, Yang R (2006) CyberC3:cybercar automated vehicles in China. In:proceedings of the 2006 transportation research board annual meeting
19. Hamner B, Koterba S, Shi J et al (2010) An autonomous mobile manipulator for assembly tasks. Auton Robot 28(1):131
20. Hu H, Gu D (2000) Landmark-based navigation of industrial mobile robots. Ind Robot 27(6):458-467
21. Kousi N, Michalos G, Makris S et al (2016) Short-term planning for part supply in assembly lines using mobile robots. In:proceedings of the 9th international conference on digital enterprise technology, 44:371-376
22. Meike D, Pellicciari M, Berselli G (2014) Energy efficient use of multirobot production lines in the automotive industry:detailed system modeling and optimization. IEEE Trans Auto Sci Eng 11(3):798-809

Tracking and localization for omni-directional mobile industrial robot using reflectors

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