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

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.

Keywords

Mobile industrial robot / Tracking and positioning / Matching

References

[1] Montemerlo M, Thrun S, Koller D. A factored solution to the simultaneous localization and mapping problem. Eighteenth Natl Conf Artif Intell, 2002, 50(2): 593-598.

[2] Lei L. Present state and future development of mobile robot technology research. Robot, 2002, 24(5): 475-480.

[3] Larsson U, Forsberg J, Wernersson A. Mobile robot localization: integrating measurements from a time-of-flight laser. IEEE Trans Ind Electron, 1996, 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. Optimal reflector selection for triangulation of robot position. Robot Auton Syst, 1998, 23(4): 277-292.

[7] Betke M, Gurvits L. Mobile localization using landmarks. IEEE Trans Robot Autom, 1997, 13(2): 251-263.

[8] Kai OA, Tomatis N, Jensen BT, et al. Multisensor on-the-fly localization: precision and reliability for applications. Robot Auton Syst, 2001, 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. Localization algorithm of autonomous mobile robot based on measuring angle. J Northeastern Univ, 2002, 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. Research of AGV localization optimization based on landmark. Transducer Microsyst Technol, 2013, 125(3): 4516-4519.

[13] Liu Y. Discussion on laser positioning algorithm of laser guidance AGV. Logist Mater Handl, 2007, 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. Efficient algorithm for mobile multicast using anycast group. IEEE Procee-Commun, 2001, 148(1): 14-18.

[16] Mendes A, Nunes U. Situation-based multi-target detection and tracking with laser-scanner in outdoor semi-structured environment. IEEE/RSJ Int Conf Intell Robot Syst, 2004, 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. An autonomous mobile manipulator for assembly tasks. Auton Robot, 2010, 28(1): 131.

[20] Hu H, Gu D. Landmark-based navigation of industrial mobile robots. Ind Robot, 2000, 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. Energy efficient use of multirobot production lines in the automotive industry: detailed system modeling and optimization. IEEE Trans Auto Sci Eng, 2014, 11(3): 798-809.

Funding

Shanghai Municipal Science and Technology Commission Grant(15550721900)