Effective Route Decision of an Automatic Moving Robot(AMR) using a 2D Spatial Map of the Stereo Camera System

2006 ◽  
Vol 20 (9) ◽  
pp. 45-53
Author(s):  
Jae-Soo Lee ◽  
Kwang-Sik Han ◽  
Jung-Hwan Ko
Keyword(s):  
Camera System ◽  
Stereo Camera

Development of an Advanced Stereo Camera System

2007 ◽  
Author(s):  
Satoshi Katahira ◽  
Eiji Shibata ◽  
Tatsuhiko Monji
Keyword(s):  
Camera System ◽  
Stereo Camera

An Experimental Analysis of the Effects of Different Hardware Setups on Stereo Camera Systems

2021 ◽  
Vol 15 (03) ◽  
pp. 337-357
Author(s):  
Alexander Julian Golkowski ◽  
Marcus Handte ◽  
Peter Roch ◽  
Pedro J. Marrón
Keyword(s):  
Experimental Analysis ◽  
Autonomous Navigation ◽  
Indoor Environments ◽  
Camera System ◽  
Stereo Camera ◽  
Camera Systems ◽  
Sensing Technology ◽  
Stereo Cameras ◽  
The Impact ◽  
General Guidance

For many application areas such as autonomous navigation, the ability to accurately perceive the environment is essential. For this purpose, a wide variety of well-researched sensor systems are available that can be used to detect obstacles or navigation targets. Stereo cameras have emerged as a very versatile sensing technology in this regard due to their low hardware cost and high fidelity. Consequently, much work has been done to integrate them into mobile robots. However, the existing literature focuses on presenting the concepts and algorithms used to implement the desired robot functions on top of a given camera setup. As a result, the rationale and impact of choosing this camera setup are usually neither discussed nor described. Thus, when designing the stereo camera system for a mobile robot, there is not much general guidance beyond isolated setups that worked for a specific robot. To close the gap, this paper studies the impact of the physical setup of a stereo camera system in indoor environments. To do this, we present the results of an experimental analysis in which we use a given software setup to estimate the distance to an object while systematically changing the camera setup. Thereby, we vary the three main parameters of the physical camera setup, namely the angle and distance between the cameras as well as the field of view and a rather soft parameter, the resolution. Based on the results, we derive several guidelines on how to choose the parameters for an application.

3D-objecttracking with a mixed omnidirectional stereo camera system

Mechatronics ◽  
2011 ◽  
Vol 21 (2) ◽  
pp. 390-398 ◽  
Author(s):  
Martin Lauer ◽  
Miriam Schönbein ◽  
Sascha Lange ◽  
Stefan Welker
Keyword(s):  
Camera System ◽  
Stereo Camera

A high precision image registration method for measurement based on the stereo camera system

Optik ◽  
2020 ◽  
Vol 204 ◽  
pp. 164186
Author(s):  
Fengkai Ke ◽  
Huanping Liu ◽  
Daxing Zhao ◽  
Guodong Sun ◽  
Wan Xu ◽  
...  
Keyword(s):  
Image Registration ◽  
High Precision ◽  
Camera System ◽  
Registration Method ◽  
Stereo Camera

scholarly journals Computational stereo camera system with programmable control loop

2011 ◽  
Vol 30 (4) ◽  
pp. 1-10 ◽  
Author(s):  
Simon Heinzle ◽  
Pierre Greisen ◽  
David Gallup ◽  
Christine Chen ◽  
Daniel Saner ◽  
...  
Keyword(s):  
Control Loop ◽  
Camera System ◽  
Stereo Camera

A Closed Form 3D Self-Positioning algorithm for a mobile robot using vision and guide-marks

Robotica ◽  
1991 ◽  
Vol 9 (3) ◽  
pp. 265-274 ◽  
Author(s):  
Zeungnam Bien ◽  
Ho Yeol Kwon ◽  
Jeongnam Youn ◽  
Il Hong Suh
Keyword(s):  
Mobile Robot ◽  
Closed Form ◽  
Walking Robot ◽  
Practical Application ◽  
Detection Mechanism ◽  
Camera System ◽  
Stereo Camera ◽  
Multiple Camera ◽  
Positioning Errors ◽  
Positioning Algorithm

SUMMARYIn this paper, the 3D self-positioning problem of a mobile robot is investigated under the assumption that there are given a set of guide points along with camera vision as the detection mechanism. The minimal number of guide points is discussed to determine the position and orientation of a mobile robot via a single or multiple camera system. For practical application, a closed form 3D self-positioning algorithm is proposed using a stereo camera system with triple guide points. It is further shown that a double triangular pattern is an effective guide-mark that is robust against measurement noise in feature extraction. Then, by simulation, the sensitivity of positioning errors due to image errors are analyzed. It is experimentally shown that the proposed method with triple guide points works well for a walking robot equipped with a stereo camera in laboratory environment.

scholarly journals Computational stereo camera system with programmable control loop

2011 ◽  
Author(s):  
Simon Heinzle ◽  
Pierre Greisen ◽  
David Gallup ◽  
Christine Chen ◽  
Daniel Saner ◽  
...  
Keyword(s):  
Control Loop ◽  
Camera System ◽  
Stereo Camera

scholarly journals Enhanced Absolute Accuracy of an Industrial Milling Robot Using Stereo Camera System

2016 ◽  
Vol 26 ◽  
pp. 389-398 ◽  
Author(s):  
Christian Möller ◽  
Hans Christian Schmidt ◽  
Nihar Hasmukhbhai Shah ◽  
Jörg Wollnack
Keyword(s):  
Absolute Accuracy ◽  
Camera System ◽  
Stereo Camera ◽  
Milling Robot
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