Abstract
The development of computer vision algorithms for navigation or object detection is one of the key issues of underwater robotics. However, extracting features from underwater images is challenging due to the presence of lighting defects, which need to be counteracted. This requires good environmental knowledge, either as a dataset or as a physic model. The lack of available data, and the high variability of the conditions, makes difficult the development of robust enhancement algorithms. A framework for the development of underwater computer vision algorithms is presented, consisting of a method for underwater imaging simulation, and an image enhancement algorithm, both integrated in the open-source robotics simulator UUV Simulator. The imaging simulation is based on a novel combination of the scattering model and style transfer techniques. The use of style transfer allows a realistic simulation of different environments without any prior knowledge of them. Moreover, an enhancement algorithm that successfully performs a correction of the imaging defects in any given scenario for either the real or synthetic images has been developed. The proposed approach showcases then a novel framework for the development of underwater computer vision algorithms for SLAM, navigation, or object detection in UUVs.
Highlights
The development of computer vision algorithms for underwater robotic platforms is gaining attention thanks to the great advances that vision capabilities have recently experienced
An image enhancement algorithm has been developed which optimizes the extraction of features from the image for any given environment, which is a key issue in localization, navigation or tracking algorithms
The framework includes an image enhancement algorithm, which optimizes the extraction of features from the image for any given environment
Summary
The development of computer vision algorithms for underwater robotic platforms is gaining attention thanks to the great advances that vision capabilities have recently experienced. They provide a wide range of utilities, from marine investigation [1,2], to archaeology [3] or structures monitoring [4,5]. A modified version of the underwater robot BlueROV2 has been used as the robotic platform for this project (see Figure 1a), equipped with low-cost sensors such as a camera and an inertial sensor This leads to the deployment of the robot being based on computer vision approaches for inspection and navigation. This work aims to develop a platform for the testing of underwater computer vision algorithms in robotic platforms
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