A stereo visual navigation method for docking autonomous underwater vehicles

Recovering and recharging autonomous underwater vehicles (AUVs) on a regular basis allows for long-term underwater activities. This research provides a vision-based navigation strategy for AUVs to independently identify and reconstruct the docking station (DS). The proposed framework includes a light beacon detection approach, a filter-based light beacon matching method, and a fusion pose estimation method for DS positioning. Four green LED light beacons are mounted symmetrically on the docking ring, enabling the stereo camera to observe them from close range. A method for detecting light beacons is proposed that assures detection accuracy by identifying false positives. On a single frame from a stereo camera, filter-based matching follows the light beacons precisely. In addition, we construct a position estimate method that significantly improves accuracy and efficiency by consisting of analyzation and iteration. A series of virtual and real-world experiments demonstrate that our methodology can provide AUVs with reliable docking navigation.

Automated summary

This research proposes a vision-based navigation strategy for AUVs to independently identify and reconstruct the docking station. The proposed framework includes methods for light beacon detection, matching, and fusion pose estimation, which can provide reliable docking navigation for AUVs.