Abstract
This paper describes development of our self-localization method in indoor environment based on LED optical frequency modulation. Full color LEDs are used as markers for position estimation. The characteristic of this system is that red, green and blue led’s optical patterns are frequency modulated independently and used them for including some kinds of information. By using the information of these optical patterns, the system can acquire all positions of the markers before the calibration. Then the time and labor for the calibration will be eliminated. In this paper, we conduct basic experiments which confirm the method to acquire the information which is provided from LED optical patterns in an actual environment.
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References
Kojima, K., Kaneko, J.: Fault tolerant calculation method of predicting road condition for network-connected wheelchair. In: Proceedings of 2017 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW 2017), pp. 345–346 (2017)
Kojima, K., Taniue, H., Kaneko, J.: Mahalanobis distance-based road condition estimation method using network-connected manual wheelchair. In: Proceedings of 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW 2016), pp. 284–285 (2016)
Kojima, K., Taniue, H., Kaneko, J.: Development of road condition categorizing system for manual wheelchair using mahalanobis distance. In: ROMANSY21 - Robot Design, Dynamics and Control, Proceedings of the 21st CISM-IFToMM Symposium. Springer, pp. 377–384 (2016)
Sato, M., Kojima, K., Kaneko, J.: Development of pavement surface inspection system for wheel chair comfortability. In: Proceedings of 2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE 2014), pp. 219–220 (2014)
Vicon Motion Capturing System Introduction. https://www.vicon.com/products Subordinate document. Cited 30 Nov 2017
OptiTrack product Introduction. https://www.optitrack.com/ Subordinate document. Cited 30 November 2017
Fontanelli, D., Ricciato, L., Soatto, S.: A fast RANSAC-based registration algorithm for accurate localization in unknown environments using LIDAR measurements. In: Proceedings of 2007 IEEE International Conference on Automation Science and Engineering, pp. 597–602. IEEE (2007)
Wan, K., Ma, L., Tan, X.: An improvement algorithm on RANSAC for image-based indoor localization. In: Proceedings of 2016 International Conference on Wireless Communications and Mobile Computing Conference (IWCMC), pp. 842–845. IEEE (2016)
He, S., Chan, S.-H.G.: Wi-Fi fingerprint-based indoor positioning: recent advances and comparisons. IEEE Commu. Surv. Tutorials 18(1), 466490 (2016)
Matsuo, K.: Implementation and experimental evaluation of an omnidirectional wheelchair for sports and moving in rooms with narrow spaces. Int. J. Space-Based Situated Comput. 7(1), 1–7 (2017)
Hayashi, M., Goshi, K., Sumida, Y., Matsunaga, K.: Development of a route finding system for manual wheelchair users based on actual measurement data. In: Proceedings of Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing (UIC/ATC), pp. 17–23 (2012)
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Kojima, K. (2018). Indoor Self Localization Method for Connected Wheelchair Based on LED Optical Frequency Modulation. In: Barolli, L., Xhafa, F., Javaid, N., Spaho, E., Kolici, V. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-75928-9_64
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DOI: https://doi.org/10.1007/978-3-319-75928-9_64
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