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.
Fiber optic shape sensing has a great potential for diverse medical and industrial applications to measure curvatures and even shapes. Featuring small footprint, strong immunity to radiation and high flexibility integration, fiber optic shape sensing opens up a new era in the fields of position tracking, human wearable devices, catheter navigation, bending detection and deformation monitoring. This paper focuses on a branch of fiber optic shape sensing techniques, with an emphasis on shape sensing based on fiber Bragg gratings (FBGs). Key technologies of shape sensing based on FBG are introduced in detail together with a critical view of its evolutionary trend. In addition, the major problems that exist in FBG shape sensing have been discussed in the end.
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