FPGA-based stereo vision system using census transform for autonomous mobile robot

2015 ◽  
Author(s):  
Kaichiro Nakazato ◽  
Yasufumi Touma ◽  
Hayato Hagiwara ◽  
Kenichi Asami ◽  
Mochimitsu Komori
Keyword(s):  
Mobile Robot ◽  
Stereo Vision ◽  
Vision System ◽  
Autonomous Mobile Robot ◽  
Census Transform ◽  
Stereo Vision System

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.

The KCLBOT: The Challenges of Stereo Vision for a Small Autonomous Mobile Robot

2012 ◽  
Author(s):  
Evangelos Georgiou ◽  
Jian S. Dai ◽  
Michael Luck
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Stereo Vision ◽  
Critical Path ◽  
Vision System ◽  
Autonomous Mobile Robots ◽  
Autonomous Mobile Robot ◽  
Sensory Data ◽  
King's College ◽  
Stereo Vision System

In small mobile robot research, autonomous platforms are severely constrained in navigation environments by the limitations of accurate sensory data to preform critical path planning, obstacle avoidance and self-localization tasks. The motivation for this work is to enable small autonomous mobile robots with a local stereo vision system that will provide an accurate reconstruction of a navigation environment for critical navigation tasks. This paper presents the KCLBOT, which was developed in King’s College London’s Centre for Robotic Research and is a small autonomous mobile robot with a stereo vision system.

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.

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 3 Bio-Mimetic Vision System For Autonomous Mobile Robot Navigation

2013 ◽  
Vol 3 (1) ◽  
pp. 4
Author(s):  
Muhammad Safwan ◽  
Muhammad Yasir Zaheen ◽  
M. Anwar Ahmed ◽  
Muhammad Shujaat Kamal ◽  
Raj Kumar
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Stereo Vision ◽  
Robot Navigation ◽  
Vision System ◽  
Experimental Results ◽  
Mobile Robot Navigation ◽  
Absolute Difference ◽  
Autonomous Mobile Robot ◽  
Dc Motors

Bio-Mimetic Vision System (BMVS) for AutonomousMobile Robot Navigation encompasses three major fields, namelyrobotics, navigation and obstacle avoidance. Bio-mimetic vision isbased on stereo vision. Summation of Absolute Difference (SAD)is applied on the images from the two cameras and disparity mapis generated which is then used to navigate and avoid obstacles.Camera calibration and SAD is applied on Matlab software.AT89C52 microcontroller, along with Matlab, is used to efficientlycontrol the DC motors mounted on the robot frame. It is observedfrom experimental results that the developed system effectivelydistinguishes objects at different distances and avoids them whenthe path is blocked.

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.

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