scholarly journals Cost-Effective Stereo Vision System for Mobile Robot Navigation and 3D Map Reconstruction

Author(s):  
Arjun B Krishnan ◽  
Jayaram Kollipara
2013 ◽  
Vol 3 (1) ◽  
pp. 4
Author(s):  
Muhammad Safwan ◽  
Muhammad Yasir Zaheen ◽  
M. Anwar Ahmed ◽  
Muhammad Shujaat Kamal ◽  
Raj Kumar

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.


2013 ◽  
Vol 1 (1) ◽  
pp. 4
Author(s):  
Muhammad Safwan ◽  
Muhammad Yasir Zaheen ◽  
M. Anwar Ahmed ◽  
Muhammad Shujaat Kamal ◽  
Raj Kumar

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.


2006 ◽  
Vol 13 (3) ◽  
pp. 203-222 ◽  
Author(s):  
V. Enescu ◽  
G. De Cubber ◽  
K. Cauwerts ◽  
H. Sahli ◽  
E. Demeester ◽  
...  

2018 ◽  
Vol 161 ◽  
pp. 03020 ◽  
Author(s):  
Ramil Safin ◽  
Roman Lavrenov ◽  
Subir Kumar Saha ◽  
Evgeni Magid

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.


2021 ◽  
Author(s):  
Jamin Islam

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.


2017 ◽  
Vol 2017 (9) ◽  
pp. 10-15 ◽  
Author(s):  
Soonhac Hong ◽  
Ming Li ◽  
Miao Liao ◽  
Peter van Beek

2015 ◽  
Vol 27 (6) ◽  
pp. 681-690 ◽  
Author(s):  
Hayato Hagiwara ◽  
◽  
Yasufumi Touma ◽  
Kenichi Asami ◽  
Mochimitsu Komori

<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.


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