Tracking of light beacons in highly turbid water and application to underwater docking

Riffat Tehseen Amjad; Mithilesh Mane; Amjad Ali Amjad; Wenmin Ge; Zejun Zhang; Jing Xu

doi:10.1117/12.2617191

30 May 2022 Tracking of light beacons in highly turbid water and application to underwater docking

Riffat Tehseen Amjad, Mithilesh Mane, Amjad Ali Amjad, Wenmin Ge, Zejun Zhang, Jing Xu

Proceedings Volume 12118, Ocean Sensing and Monitoring XIV; 121180A (2022) https://doi.org/10.1117/12.2617191
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

The use of autonomous underwater vehicles (AUVs), to potentially carry out underwater exploration missions, is limited due to insufficient onboard battery and data storage capacity. To overcome this problem, underwater docking stations are used to provide the facility of underwater charging and data transfer for AUVs. These docking stations are designed to be installed in the dynamic ocean environment, where the turbidity and low-light conditions are key challenges to hinder the successful docking operation. The vision guidance algorithms based on active or passive markers are typically used to precisely guide the AUV towards the docking station. In this paper, we propose a vision-based guidance method, using lock-in detection, to mitigate the effect of turbidity, and to reject the unwanted light sources or noisy luminaries, simultaneously. The lock-in detection method locks on the blinking frequency of light beacons located at the docking station and successfully vanishes the effect of unwanted light at other frequencies. The proposed method uses two light beacons, emitting at a fixed frequency, installed at the simulated docking station and a single CMOS camera. Proof-of-the-concept experiments are performed to show the validity of the proposed approach. The obtained results show that our method is capable of recognizing the light beacons at different turbidity levels, and it can efficiently reject the unwanted light without using separate image processing for this step of the vision-based guidance algorithm. The effectiveness of the proposed method is validated by calculating the true positive rate of the detection method at each turbidity level.

Conference Presentation

Citation Download Citation

Riffat Tehseen Amjad, Mithilesh Mane, Amjad Ali Amjad, Wenmin Ge, Zejun Zhang, and Jing Xu "Tracking of light beacons in highly turbid water and application to underwater docking", Proc. SPIE 12118, Ocean Sensing and Monitoring XIV, 121180A (30 May 2022); https://doi.org/10.1117/12.2617191

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