Distance measurement error compensation using machine learning for laser scanning AMCW time-of-flight sensor

Sung-Hyun Lee; Wook-Hyeon Kwon; Yoon-Seop Lim; Yong-Hwa Park

doi:10.1117/12.2610458

1 March 2022 Distance measurement error compensation using machine learning for laser scanning AMCW time-of-flight sensor

Sung-Hyun Lee, Wook-Hyeon Kwon, Yoon-Seop Lim, Yong-Hwa Park

Author Affiliations +

Proceedings Volume 12013, MOEMS and Miniaturized Systems XXI; 1201303 (2022) https://doi.org/10.1117/12.2610458
Event: SPIE OPTO, 2022, San Francisco, California, United States

Abstract

Amplitude-modulated continuous wave (AMCW) time-of-flight (ToF) sensor is widely used to capture 3D information of objects due to its relatively high measurement precision in short range. However, the measurement accuracy of AMCW ToF measurement method is generally sensitive to the reflectivity of object, internal stray light, modulation instability, and external light. Consequently, distance measurement error inevitably occurs even in indoor measurement condition. To compensate such error, a post processing method based on machine learning is proposed in this paper. This data driven correction method is validated under indoor measurement condition. According to the experimental results, the distance measurement error correction method presented in this paper shows the most high accuracy compared to other related research results.

Conference Presentation

Citation Download Citation

Sung-Hyun Lee, Wook-Hyeon Kwon, Yoon-Seop Lim, and Yong-Hwa Park "Distance measurement error compensation using machine learning for laser scanning AMCW time-of-flight sensor", Proc. SPIE 12013, MOEMS and Miniaturized Systems XXI, 1201303 (1 March 2022); https://doi.org/10.1117/12.2610458

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