Self Calibration of a Sonar–Vision System for Underwater Vehicles: A New Method and a Dataset

Abstract

Monocular cameras and multibeam imaging sonars are common sensors of Unmanned Underwater Vehicles (UUV). In this paper, we propose a new method for calibrating a hybrid sonar–vision system. This method is based on motion comparisons between both images and allows us to compute the transformation matrix between the camera and the sonar and to estimate the camera’s focal length. The main advantage of our method lies in performing the calibration without any specific calibration pattern, while most other existing methods use physical targets. In this paper, we also propose a new sonar–vision dataset and use it to prove the validity of our calibration method.

Advanced Underwater Measurement System for ROVs: Integrating Sonar and Stereo Vision for Enhanced Subsea Infrastructure Maintenance

“…For the fusion model, Negahdaripour et al presented the epipolar geometry of an optical-acoustic stereo imaging system for underwater inspections [23]. Pecheux et al used motion comparisons between images from the monocular camera and multibeam imaging sonar to compute the transformation matrix between the camera and the sonar and estimate the camera's focal length [24]. While significant progress has been made in the field of robot navigation through the integration of acoustic and optical sensors, there remains substantial untapped potential in the realm of precision ranging techniques.…”