Robust and Accurate Detection of Object Orientation and ID Without Color Segmentation

Shimizu, Shoichi; Nagahashi, Tomoyuki; Fujiyoshi, Hironobu

doi:10.1007/11780519_36

Cited by 5 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Common methods used for the MR identification are based in targets placed around the body of each robot. These targets (marks) are placed with different configurations or colours to identify precisely each robot [1,2,3].…”

Section: Robots Recognition In An Ispacementioning

confidence: 99%

Service oriented architecture for mobile robot localization

Christo

Cardeira

2007

2007 IEEE Conference on Emerging Technologies &Amp; Factory Automation (EFTA 2007)

View full text Add to dashboard Cite

Sensors networks with some intelligence have been proposed for supporting mobile robot navigation systems in indoor environments. However, a standard method of communication among the sensor networks and the mobile robots still doesn't exist and the introduction of new robots in a certain environment can be a difficult task.In this paper, we present a practical example that uses the emerging standard Web Services technology for communication and seamless integration of mobile robots and intelligent sensor networks, which is used for robot localization purposes.

show abstract

Section: Robots Recognition In An Ispacementioning

confidence: 99%

Service oriented architecture for mobile robot localization

Christo

Cardeira

2007

2007 IEEE Conference on Emerging Technologies &Amp; Factory Automation (EFTA 2007)

View full text Add to dashboard Cite

show abstract

“…This procedure is used for finding the center of the colored marking patterns on the top of each robot -the red shape seen on figure 2-b. Identification and orientation: The process here described is inspired on [5]. Once a potential blob is found, a radial pattern of colors is sampled within a predefined radius of its center.…”

Section: The Position Feedbackmentioning

confidence: 99%

Introducing Physical Visualization Sub-league

Guerra¹,

Boedecker²,

Mayer

et al. 2008

Lecture Notes in Computer Science

View full text Add to dashboard Cite

This work introduces the new sub-league of the RoboCup Soccer Simulation League, called Physical Visualization. We show how the fundamental collaborative concepts of this new sub-league shift essential research issues from the playing agents themselves to the development of a new versatile research and educational platform. Additionally, we discuss benefits of this new platform in terms of standardization, flexibility and reasonable price. We also try to characterize and discuss the place of this new sub-league within the RoboCup community. Finally, competition formats and roadmaps are presented and discussed.

show abstract

“…For this purpose we have developed a fast edge detection algorithm that can be used in conjunction with a border following algorithm so that we do not have to process all of the edges in the entire image. A large proportion of the machine vision literature of recent times, both in RoboCup and elsewhere (Gunnarsson et al, 2005;Shimizu et al, 2005;Kak & DeSouza, 2002), has attempted to address the problem of dynamic illumination conditions. We present a viable solution here, provided that the conditions are not too widely variable.…”

Section: Introductionmentioning

confidence: 99%