Stereo Vision System for Vision-Based Control of Inspection-Class ROVs

The inspection-class Remotely Operated Vehicles (ROVs) are crucial in underwater inspections. Their prime function is to allow the replacing of humans during risky subaquatic operations. These vehicles gather videos from underwater scenes that are sent online to a human operator who provides control. Furthermore, these videos are used for analysis. This demands an RGB camera operating at a close distance to the observed objects. Thus, to obtain a detailed depiction, the vehicle should move with a constant speed and a measured distance from the bottom. As very few inspection-class ROVs possess navigation systems that facilitate these requirements, this study had the objective of designing a vision-based control method to compensate for this limitation. To this end, a stereo vision system and image-feature matching and tracking techniques were employed. As these tasks are challenging in the underwater environment, we carried out analyses aimed at finding fast and reliable image-processing techniques. The analyses, through a sequence of experiments designed to test effectiveness, were carried out in a swimming pool using a VideoRay Pro 4 vehicle. The results indicate that the method under consideration enables automatic control of the vehicle, given that the image features are present in stereo-pair images as well as in consecutive frames captured by the left camera.

Study of the Error Caused by Camera Movement for the Stereo-Vision System

The stereo-vision system plays an increasingly important role in various fields of research and applications. However, inevitable slight movements of cameras under harsh working conditions can significantly influence the 3D measurement accuracy. This paper focuses on the effect of camera movements on the stereo-vision 3D measurement. The camera movements are divided into four categories, viz., identical translations and rotations, relative translation and rotation. The error models of 3D coordinate and distance measurement are established. Experiments were performed to validate the mathematical models. The results show that the 3D coordinate error caused by identical translations increases linearly with the change in the positions of both cameras, but the distance measurement is not affected. For identical rotations, the 3D coordinate error introduced only in the rotating plane is proportional to the rotation angle within 10° while the distance error is zero. For relative translation, both coordinate and distance errors keep linearly increasing with the change in the relative positions. For relative rotation, the relationship between 3D coordinate error and rotation angle can be described as the nonlinear trend similar to a sine-cosine curve. The impact of the relative rotation angle on distance measurement accuracy does not increase monotonically. The relative rotation is the main factor compared to other cases. Even for the occurrence of a rotation angle of 10°, the resultant maximum coordinate error is up to 2000 mm, and the distance error reaches 220%. The results presented are recommended as practice guidelines to reduce the measurement errors.

Architecture and implementation of a high frame-rate stereo vision system

For the purpose of autonomous satellite grasping, a high-speed, low-cost stereo vision system is required with high accuracy. This type of system must be able to detect an object and estimate its range. Hardware solutions are often chosen over software solutions, which tend to be too slow for high frame-rate applications. Designs utilizing field programmable gate arrays (FPGAs) provide flexibility and are cost effective versus solutions that provide similar performance (i.e., Application Specific Integrated Circuits). This thesis presents the architecture and implementation of a high frame-rate stereo vision system based on an FPGA platform. The system acquires stereo images, performs stereo rectification and generates disparity estimates at frame-rates close to 100 fpSi and on a large-enough FPGA, it can process 200 fps. The implementation presents novelties in performance and in the choice of the algorithm implemented. It achieves superior performance to existing systems that estimate scene depth. Furthermore, it demonstrates equivalent accuracy to software implementations of the dynamic programming maximum likelihood stereo correspondence algorithm.

Architecture and implementation of a high frame-rate stereo vision system

For the purpose of autonomous satellite grasping, a high-speed, low-cost stereo vision system is required with high accuracy. This type of system must be able to detect an object and estimate its range. Hardware solutions are often chosen over software solutions, which tend to be too slow for high frame-rate applications. Designs utilizing field programmable gate arrays (FPGAs) provide flexibility and are cost effective versus solutions that provide similar performance (i.e., Application Specific Integrated Circuits). This thesis presents the architecture and implementation of a high frame-rate stereo vision system based on an FPGA platform. The system acquires stereo images, performs stereo rectification and generates disparity estimates at frame-rates close to 100 fpSi and on a large-enough FPGA, it can process 200 fps. The implementation presents novelties in performance and in the choice of the algorithm implemented. It achieves superior performance to existing systems that estimate scene depth. Furthermore, it demonstrates equivalent accuracy to software implementations of the dynamic programming maximum likelihood stereo correspondence algorithm.