Accurate real-time ball trajectory estimation with onboard stereo camera system for humanoid ping-pong robot

2018 ◽  
Vol 101 ◽  
pp. 34-44 ◽  
Author(s):  
Yong Liu ◽  
Liang Liu
Keyword(s):  
Real Time ◽  
Camera System ◽  
Trajectory Estimation ◽  
Stereo Camera ◽  
Ping Pong ◽  
Ball Trajectory

Real-Time 3D Ball Trajectory Estimation for RoboCup Middle Size League Using a Single Camera

2012 ◽  
pp. 586-597 ◽  
Author(s):  
Hugo Silva ◽  
André Dias ◽  
José Almeida ◽  
Alfredo Martins ◽  
Eduardo Silva
Keyword(s):  
Real Time ◽  
Single Camera ◽  
Trajectory Estimation ◽  
Ball Trajectory

Real-time 2D height mapping method for an unmanned vehicle using a stereo camera and laser sensor fusion

2012 ◽  
Vol 10 (4) ◽  
pp. 761-771 ◽  
Author(s):  
Jeong-Hyun Kim ◽  
Young-Zhu Yoon ◽  
Sun-Cheol Yu ◽  
Dong-Joong Kang
Keyword(s):  
Real Time ◽  
Sensor Fusion ◽  
Mapping Method ◽  
Laser Sensor ◽  
Unmanned Vehicle ◽  
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.

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