Abstract
In this paper, we propose a novel vision-based humanoid control method and visual tracking based on constant velocity (CV) model using the finite impulse response (FIR) filter. The proposed method has robust performance even if a sampling time or noise information is inaccurate. Furthermore, even when the movement of the detected ball or the ambient illuminance changes suddenly, the proposed method shows robust performance. The robust performance of the proposed method is verified through experimental results.
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References
Kang, T.K., Mo, Y.K., Pae, D.S., Ahn, C.K., Lim, M.T.: Robust visual tracking framework in the presence of blurring by arbitrating appearance and feature-based detection. Measurement 95, 50–69 (2017)
Weng, S.K., Kuo, C.M., Tu, S.K.: Video object tracking using adaptive kalman filter. J. Vis. Commun. Image Represent. 17(6), 1190–1208 (2006)
Pak, J.M., Ahn, C.K., Mo, Y.K., Lim, M.T., Song, M.K.: Maximum likelihood FIR filter for visual object tracking. Neurocomputing 216, 543–553 (2016)
Choi, I.H., Pak, J.M., Ahn, C.K., Lee, S.H., Lim, M.T., Song, M.K.: Arbitration algorithm of FIR filter and optical flow based on ANFIS for visual object tracking. Measurement 75, 338–353 (2015)
Choi, I.H., Pak, J.M., Ahn, C.K., Mo, Y.K., Lim, M.T., Song, M.K.: New preceding vehicle tracking algorithm based on optimal unbiased finite memory filter. Measurement 73, 262–274 (2015)
Pak, J.M., Ahn, C.K., Shmaliy, Y.S., Lim, M.T.: Improving reliability of particle filter-based localization in wireless sensor networks via hybrid particle/FIR filtering. IEEE Trans. Ind. Inform. 11(5), 1089–1098 (2015)
Ahn, C.K., Shi, P., Basin, M.V.: Deadbeat dissipative FIR filtering. IEEE Trans. Circuits Syst. I 63(8), 1210–1221 (2016)
Acknowledgments
This work was supported in part by “Human Resources program in Energy Technology” of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20174030201820) and in part by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT&Future Planning (NRF - 2017R1A1A1A05001325).
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Kim, K.S., Kang, H.H., You, S.H., Ahn, C.K. (2018). Vision-Based Humanoid Robot Control Using FIR Filter. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_205
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DOI: https://doi.org/10.1007/978-981-10-7605-3_205
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