A Novel Approach to Ball Detection for Humanoid Robot Soccer

Budden, David; Fenn, Shannon; Walker, Josiah; Mendes, Alexandre

doi:10.1007/978-3-642-35101-3_70

Cited by 18 publications

(7 citation statements)

References 8 publications

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“…Since 1997, researchers and competitors have decomposed this ambitious pursuit into two complementary categories [2]: -Physical robot league: Using physical robots to play soccer games. This category now contains many different leagues for both wheeled robots (small-sized [3] and mid-sized leagues [4]) and humanoids (standard platform league [5] and humanoid league [6]), with each focusing on different aspects of physical robot design [7], motor control and bipedal locomotion [8,9], real-time localisation [10,11] and computer vision [12,13,14]. -Software agent league: Using software or synthetic agents to play soccer games on an official soccer server over a network.…”

Section: The Robocup Humanoid Challengementioning

confidence: 99%

Simulation Leagues: Analysis of Competition Formats

Budden

Obst

Prokopenko

2015

RoboCup 2014: Robot World Cup XVIII

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The selection of an appropriate competition format is critical for both the success and credibility of any competition, both real and simulated. In this paper, the automated parallelism offered by the RoboCupSoccer 2D simulation league is leveraged to conduct a 28,000 game round-robin between the top 8 teams from RoboCup 2012 and 2013. A proposed new competition format is found to reduce variation from the resultant statistically significant team performance rankings by 75% and 67%, when compared to the actual competition results from RoboCup 2012 and 2013 respectively. These results are statistically validated by generating 10,000 random tournaments for each of the three considered formats and comparing the respective distributions of ranking discrepancy.

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Section: The Robocup Humanoid Challengementioning

confidence: 99%

Simulation Leagues: Analysis of Competition Formats

Budden

Obst

Prokopenko

2015

RoboCup 2014: Robot World Cup XVIII

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“…Valid transitions representing a ball are "orange→all colours" or "all colours→orange". The method is very efficient; accurate in terms of distance-to-ball estimation; and robust to partial occlusion (up to 50%) of the ball [16].…”

Section: Ballmentioning

confidence: 99%

Addressing the non-functional requirements of computer vision systems: a case study

Fenn

Mendes

Budden

2015

Machine Vision and Applications

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Computer vision plays a major role in the robotics industry, where vision data is frequently used for navigation and high-level decision making. Although there is significant research in algorithms and functional requirements, there is a comparative lack of emphasis on how best to map these abstract concepts onto an appropriate software architecture.In this study, we distinguish between the functional and non-functional requirements of a computer vision system. Using a RoboCup humanoid robot system as a case study, we propose and develop a software architecture that fulfills the latter criteria.The modifiability of the proposed architecture is demonstrated by detailing a number of feature detection algorithms and emphasizing which aspects of the underlying framework were modified to support their integration. To demonstrate portability, we port our vision system (designed for an application-specific DARwIn-OP humanoid robot) to a general-purpose, Raspberry Pi computer. We evaluate performance on both platforms and compare them to a vision system optimised for functional requirements only.The architecture and implementation presented in this study provide a highly generalisable framework for computer vision system design that is of particular benefit in research and development, competition and other environments in which rapid system evolution is necessary.

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“…Publications are available e.g. from [5,6,20,30,32,19,15,7,10]. Localisation and Kalman Filters: Research on the topic of localisation focused on Bayesian approaches to robot localisation including Kalman Filter and particle filter based methods.…”

Section: Research Areasmentioning

confidence: 99%

The NUbots Team Description Paper 2015

Walker¹,

Houliston²,

Annable³

et al. 2015

Preprint

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The NUbots are an interdisciplinary RoboCup team from The University of Newcastle, Australia. The team has a history of strong contributions in the areas of machine learning and computer vision. The NUbots have participated in RoboCup leagues since 2002, placing first several times in the past. In 2014 the NUbots also partnered with the University of Newcastle Mechatronics Laboratory to participate in the RobotX Marine Robotics Challenge, which resulted in several new ideas and improvements to the NUbots vision system for RoboCup. This paper summarizes the history of the NUbots team, describes the roles and research of the team members, gives an overview of the NUbots' robots, their software system, and several associated research projects.

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A Novel Approach to Ball Detection for Humanoid Robot Soccer

Cited by 18 publications

References 8 publications

Simulation Leagues: Analysis of Competition Formats

Simulation Leagues: Analysis of Competition Formats

Addressing the non-functional requirements of computer vision systems: a case study

The NUbots Team Description Paper 2015

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