FPGA-Based Stereo Vision System Using Gradient Feature Correspondence

2015 ◽  
Vol 27 (6) ◽  
pp. 681-690 ◽  
Author(s):  
Hayato Hagiwara ◽  
◽  
Yasufumi Touma ◽  
Kenichi Asami ◽  
Mochimitsu Komori
Keyword(s):  
Mobile Robot ◽  
Stereo Vision ◽  
Vision System ◽  
Image Feature ◽  
Interest Point ◽  
Feature Correspondence ◽  
Speeded Up Robust Features ◽  
Stereo Vision System ◽  
Simpler Algorithm ◽  
Gradient Feature

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270006/10.jpg"" width=""300"" /> Mobile robot with a stereo vision</div>This paper describes an autonomous mobile robot stereo vision system that uses gradient feature correspondence and local image feature computation on a field programmable gate array (FPGA). Among several studies on interest point detectors and descriptors for having a mobile robot navigate are the Harris operator and scale-invariant feature transform (SIFT). Most of these require heavy computation, however, and using them may burden some computers. Our purpose here is to present an interest point detector and a descriptor suitable for FPGA implementation. Results show that a detector using gradient variance inspection performs faster than SIFT or speeded-up robust features (SURF), and is more robust against illumination changes than any other method compared in this study. A descriptor with a hierarchical gradient structure has a simpler algorithm than SIFT and SURF descriptors, and the result of stereo matching achieves better performance than SIFT or SURF.

scholarly journals Experiments on mobile robot stereo vision system calibration under hardware imperfection

2018 ◽  
Vol 161 ◽  
pp. 03020 ◽  
Author(s):  
Ramil Safin ◽  
Roman Lavrenov ◽  
Subir Kumar Saha ◽  
Evgeni Magid
Keyword(s):  
Mobile Robot ◽  
Stereo Vision ◽  
Experimental Approach ◽  
Vision System ◽  
Robot Vision ◽  
System Calibration ◽  
Stereo Vision System ◽  
Calibration Methods ◽  
Vertical Level ◽  
Grid Based

Calibration is essential for any robot vision system for achieving high accuracy in deriving objects metric information. One of typical requirements for a stereo vison system in order to obtain better calibration results is to guarantee that both cameras keep the same vertical level. However, cameras may be displaced due to severe conditions of a robot operating or some other circumstances. This paper presents our experimental approach to the problem of a mobile robot stereo vision system calibration under a hardware imperfection. In our experiments, we used crawler-type mobile robot «Servosila Engineer». Stereo system cameras of the robot were displaced relative to each other, causing loss of surrounding environment information. We implemented and verified checkerboard and circle grid based calibration methods. The two methods comparison demonstrated that a circle grid based calibration should be preferred over a classical checkerboard calibration approach.

Positioning Autonomous Mobile Robot Based on Measurements Onboard Digital Stereo Vision System

2014 ◽  
Vol 2 (2) ◽  
pp. 37-77 ◽  
Author(s):  
Sergey Valentinovich Kravtsov ◽  
Konstantin Evgenjevich Rumjantsev
Keyword(s):  
Stochastic Model ◽  
Mobile Robot ◽  
Stereo Vision ◽  
Measurement Errors ◽  
Vision System ◽  
Digital System ◽  
Autonomous Mobile Robot ◽  
Measuring Instrument ◽  
Stereo Vision System ◽  
Communication Dynamics

The problem of local positioning of autonomous mobile robot acting on an unknown scene. The measuring instrument is analyzed on-board stereo vision system consisting of two collinear digital camcorders. The description of the measurement space of digital stereo vision, proposed a stochastic model of the measurement errors of point features scenes. The problem of optimizing the choice of reference for local positioning of autonomous mobile robot. A method for communication dynamics of movement of the mobile robot with the parameters of the digital system stereovision.

A New Mobile Robot With a Passive Mechanism and a Stereo Vision System for Hazardous Terrain Exploration

2004 ◽  
Author(s):  
Sukjune Yoon ◽  
Chun-Kyu Woo ◽  
Hyun Do Choi ◽  
Sung-Kee Park ◽  
Sung-Chul Kang ◽  
...  
Keyword(s):  
Remote Control ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Stereo Vision ◽  
High Speed ◽  
Vision System ◽  
Three Dimensional ◽  
Linkage Mechanism ◽  
Passive Mechanism ◽  
Stereo Vision System

The purpose of this project is to develop a mobile robot for hazardous terrain exploration. The exploration of hazardous terrain requires the development of a passive mechanism adaptable to such terrain and a sensing system for obstacle avoidance, as well as a remote control. We designed a new mobile robot, the Ronahz 6-wheel robot, which uses a passive mechanism that can adapt to hazardous terrains and building stairways without any active control. The suggested passive linkage mechanism consists of a simple four-bar linkage mechanism. In addition, we install a stereo vision system for obstacle avoidance, as well as a remote control. Wide dynamic range CCD cameras are used for outdoor navigation. A stereo vision system commonly requires high computational power. Therefore, we use a new high-speed stereo correspondence algorithm, triangulation, and iterative closest point (ICP) registration to reduce computation time. Disparity maps computed by a newly proposed, high-speed method are sent to the operator by a wireless LAN equipment. At the remote control site, a three-dimensional digital map around a mobile robot is built by ICP registration and reconstruction process, and this three-dimensional map is displayed for the operator. This process allows the operator to sense the environment around the robot and to give commands to the mobile robot when the robot is in a remote site.

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

2021 ◽  
Vol 13 (24) ◽  
pp. 5075
Author(s):  
Stanisław Hożyń ◽  
Bogdan Żak
Keyword(s):  
Stereo Vision ◽  
Feature Matching ◽  
Control Method ◽  
Vision System ◽  
Image Features ◽  
Image Feature ◽  
Stereo Pair ◽  
Navigation Systems ◽  
Stereo Vision System ◽  
Vision Based Control

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.

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