scholarly journals Vision System of Mobile Robot Combining Binocular and Depth Cameras

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yuxiang Yang ◽  
Xiang Meng ◽  
Mingyu Gao
Keyword(s):  
Mobile Robot ◽  
3D Reconstruction ◽  
Trajectory Planning ◽  
Stereo Matching ◽  
Vision System ◽  
Depth Camera ◽  
Structural Constraints ◽  
Depth Cameras ◽  
Stereo Cameras ◽  
Binocular Stereo

In order to optimize the three-dimensional (3D) reconstruction and obtain more precise actual distances of the object, a 3D reconstruction system combining binocular and depth cameras is proposed in this paper. The whole system consists of two identical color cameras, a TOF depth camera, an image processing host, a mobile robot control host, and a mobile robot. Because of structural constraints, the resolution of TOF depth camera is very low, which difficultly meets the requirement of trajectory planning. The resolution of binocular stereo cameras can be very high, but the effect of stereo matching is not ideal for low-texture scenes. Hence binocular stereo cameras also difficultly meet the requirements of high accuracy. In this paper, the proposed system integrates depth camera and stereo matching to improve the precision of the 3D reconstruction. Moreover, a double threads processing method is applied to improve the efficiency of the system. The experimental results show that the system can effectively improve the accuracy of 3D reconstruction, identify the distance from the camera accurately, and achieve the strategy of trajectory planning.

Research of Stereo Matching Based on HALCON

2013 ◽  
Vol 415 ◽  
pp. 361-364
Author(s):  
Hui Yu Xiang ◽  
Zhe Li ◽  
Jia Jun Huang ◽  
Baoan Han
Keyword(s):  
Image Matching ◽  
Stereo Matching ◽  
Vision System ◽  
Difficult Problem ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Matching Window

Binocular stereo matching is a hot and difficult problem in machine vision. In this paper, based on the matching method of Halcon which is visual software perform image matching. First, performing binocular stereo vision system calibration, based on the calibration results acquired the epipolar standard geometric structure. Then, image matching researched under this structure. At last, using ncc matching algorithm, through comparing the different parameters matching window obtain ideal match results. Experiments prove that this method not only can effectively shorten matching time, but also can achieve higher matching accuracy.

Fast, Accurate, and Automated 3D Reconstruction Using a Depth Camera Mounted on an Industrial Robot

2021 ◽  
Author(s):  
Rishi Malhan ◽  
Rex Jomy Joseph ◽  
Prahar M. Bhatt ◽  
Brual Shah ◽  
Satyandra K. Gupta
Keyword(s):  
3D Reconstruction ◽  
Cycle Time ◽  
Industrial Robot ◽  
Low Cost ◽  
Point Clouds ◽  
Industrial Robots ◽  
Depth Camera ◽  
Reconstruction Process ◽  
Depth Cameras ◽  
Manufacturing Applications

Abstract 3D reconstruction technology is used in a wide variety of applications. Currently, automatically creating accurate pointclouds for large parts requires expensive hardware. We are interested in using low-cost depth cameras mounted on commonly available industrial robots to create accurate pointclouds for large parts automatically. Manufacturing applications require fast cycle times. Therefore, we are interested in speeding up the 3D reconstruction process. We present algorithmic advances in 3D reconstruction that achieve a sub-millimeter accuracy using a low-cost depth camera. Our system can be used to determine a pointcloud model of large and complex parts. Advances in camera calibration, cycle time reduction for pointcloud capturing, and uncertainty estimation are made in this work. We continuously capture point-clouds at an optimal camera location with respect to part distance during robot motion execution. The redundancy in pointclouds achieved by the moving camera significantly reduces errors in measurements without increasing cycle time. Our system produces sub-millimeter accuracy.

scholarly journals AN AUTOMATIC 3D RECONSTRUCTION METHOD BASED ON MULTI-VIEW STEREO VISION FOR THE MOGAO GROTTOES

2015 ◽  
Vol XL-4/W5 ◽  
pp. 171-176 ◽  
Author(s):  
J. Xiong ◽  
S. Zhong ◽  
L. Zheng
Keyword(s):  
3D Reconstruction ◽  
Stereo Vision ◽  
Measurement System ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Texture Mapping ◽  
Reconstruction Method ◽  
Epipolar Constraint ◽  
Mogao Grottoes ◽  
Binocular Stereo

This paper presents an automatic three-dimensional reconstruction method based on multi-view stereo vision for the Mogao Grottoes. 3D digitization technique has been used in cultural heritage conservation and replication over the past decade, especially the methods based on binocular stereo vision. However, mismatched points are inevitable in traditional binocular stereo matching due to repeatable or similar features of binocular images. In order to reduce the probability of mismatching greatly and improve the measure precision, a portable four-camera photographic measurement system is used for 3D modelling of a scene. Four cameras of the measurement system form six binocular systems with baselines of different lengths to add extra matching constraints and offer multiple measurements. Matching error based on epipolar constraint is introduced to remove the mismatched points. Finally, an accurate point cloud can be generated by multi-images matching and sub-pixel interpolation. Delaunay triangulation and texture mapping are performed to obtain the 3D model of a scene. The method has been tested on 3D reconstruction several scenes of the Mogao Grottoes and good results verify the effectiveness of the method.

scholarly journals 3D Vision System for a Robotic Arm Based on Equal Baseline Camera Array

2019 ◽  
Vol 99 (1) ◽  
pp. 13-28
Author(s):  
Adam L. Kaczmarek
Keyword(s):  
Stereo Matching ◽  
Vision System ◽  
Robotic Arm ◽  
Light Conditions ◽  
3D Vision ◽  
Measuring Devices ◽  
Camera Array ◽  
Stereo Cameras ◽  
3D Scanners ◽  
Disparity Maps

AbstractThis paper presents a lightweight 3D vision system called Equal Baseline Camera Array (EBCA). EBCA can work in different light conditions and it can be applied for measuring large range of distances. The system is a useful alternative to other known distance measuring devices such as structured-light 3D scanners, time-of-flight cameras, Light Detection and Ranging (LIDAR) devices and structure from motion techniques. EBCA can be mounted on a robotic arm without putting significant load on its construction. EBCA consists of a central camera and a ring of side cameras. The system uses stereo matching algorithms to acquire disparity maps and depth maps similarly as in case of using stereo cameras. This paper introduces methods of adapting stereo matching algorithms designed for stereo cameras to EBCA. The paper also presents the analysis of local, semi-global and global stereo matching algorithms in the context of the EBCA usage. Experiments show that, on average, results obtained from EBCA contain 37.49% less errors than the results acquired from a single stereo camera used in the same conditions.

Down-the-Hole Drill Position Based on Mechanical Mechanics and Binocular Stereo Vision

2014 ◽  
Vol 908 ◽  
pp. 291-295
Author(s):  
Wan Rong Wu ◽  
Jian Shi
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Membership Functions ◽  
Test Bed ◽  
Threshold Method ◽  
Invariant Moment ◽  
Stereo Vision System ◽  
Binocular Stereo Vision ◽  
Stereo Cameras ◽  
Binocular Stereo

A new down-the-hole drill (DTH) position method based on binocular stereo vision was presented. In this method, a pair of stereo images containing holes marker were obtained by stereo cameras, which were then segmented by the fuzzy threshold method based on trapezoidal membership functions. The hole mark centre was extracted by image invariant moment principle. Then hole mark 3D locations can be calculated by triangulation principle. Finally, the autonomous position experiments based on binocular stereo vision system were implemented on DTH test-bed. The experiments results show that the binocular stereo vision system applied to DTH drill position is reliable, and the position error is within 25mm.

ALGORITHMS FOR IMPROVING SPEED AND ACCURACY OF AUTOMATED 3D RECONSTRUCTION WITH A DEPTH CAMERA MOUNTED ON AN INDUSTRIAL ROBOT

2021 ◽  
pp. 1-13
Author(s):  
Rishi K. Malhan ◽  
Rex Jomy Joseph ◽  
Prahar Bhatt ◽  
Brual Shah ◽  
Satyandra K. Gupta
Keyword(s):  
3D Reconstruction ◽  
Cycle Time ◽  
Industrial Robot ◽  
Low Cost ◽  
Industrial Robots ◽  
Depth Camera ◽  
Reconstruction Process ◽  
Depth Cameras ◽  
Camera Location ◽  
Manufacturing Applications

Abstract 3D reconstruction technology is used in a wide variety of applications. Currently, automatically creating accurate pointclouds for large parts requires expensive hardware. We are interested in using low-cost depth cameras mounted on commonly available industrial robots to create accurate pointclouds for large parts automatically. Manufacturing applications require fast cycle times. Therefore, we are interested in speeding up the 3D reconstruction process. We present algorithmic advances in 3D reconstruction that achieve a sub-millimeter accuracy using a low-cost depth camera. Our system can be used to determine a pointcloud model of large and complex parts. Advances in camera calibration, cycle time reduction for pointcloud capturing, and uncertainty estimation are made in this work. We continuously capture pointclouds at an optimal camera location with respect to part distance during robot motion execution. The redundancy in pointclouds achieved by the moving camera significantly reduces errors in measurements without increasing cycle time. Our system produces sub-millimeter accuracy.

scholarly journals 3D Reconstruction Algorithm of Weld Pool Surface Based on Computer Vision Technology

2015 ◽  
Vol 9 (1) ◽  
pp. 820-825
Author(s):  
Zhen-Hai Mu
Keyword(s):  
3D Reconstruction ◽  
Weld Pool ◽  
Stereo Matching ◽  
Vision System ◽  
Reconstruction Algorithm ◽  
Welding Parameters ◽  
Matching Algorithm ◽  
Pool Surface ◽  
Matching Cost ◽  
Weld Pool Surface

As is well known that sensing and measuring the weld pool surface is very important to design intelligent welding machines which is able to imitate a skilled human welder who can choose suitable welding parameters. Therefore, in this paper, we focused on the problem of weld pool surface 3D reconstruction, which is a key issue in intelligent welding machines development. Firstly, the framework of the weld pool surface 3D reconstruction system is described. The weld pool surface 3D reconstruction system uses a single camera stereo vision system to extract original data from weld pool, and then the left and right images are collected. Afterward, we utilize Pixel difference square and matching algorithm and Stereo matching algorithm to process images. Next, the 3D reconstruction of weld pool surface is constructed using the point cloud data. Secondly, stereo matching based weld pool surface 3D reconstruction algorithm is illustrated. In this algorithm, the matching cost function is computed through the Markov random field, and then the weighted matching cost is calculated via the guided filter. Thirdly, to test the performance of our proposed algorithm, we develop an experimental platform to measure weld pool width, length, convexity and the previous inputs based on a linear model predictive controller. Experimental results demonstrate that the proposed 3D reconstruction algorithm of weld pool surface can achieve high quality under both current disturbance and speed disturbance.

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