Strategy for collaboration in robot soccer

Sng, H.L.; Gupta, Gourab Sen; Messom, Chris

doi:10.1109/delta.2002.994644

Cited by 26 publications

(16 citation statements)

References 3 publications

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“…In [3], for example, the potential field theory was used so that the robot was attracted to the ball and repelled by other robots within the field. In [4], the fuzzy logic is used to decide which robot should attack the ball from the analysis of certain parameters. Another technique often used to implement game strategies is the state transition, as used by the Carrossel Caipira team [5], for example.…”

Section: Introductionmentioning

confidence: 99%

A Methodology to Designing Strategies for Robot Soccer Based on Discrete Event Systems Formalism

Cardoso

Molina

Freire

et al. 2012

2012 Brazilian Robotics Symposium and Latin American Robotics Symposium

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In the robot soccer, a good strategy is essential to the success of a team. It is responsible to define the behavior of each robot on the many game situations and make the team play in a cooperative manner to win the game. To accomplish this, it is proposed in this paper a methodology to designing strategies for robot soccer based on discrete event systems formalism. The main idea is to allow the construction of a game strategy where the behavior of each robot can be dynamically modified, depending on the context of the match. This strategy is modeled based on the discrete events system (DES) theory. The DES formalism enables to implement the interaction between the various behaviors of a system in a simple way, allowing the addition of new behavior without changing the current behaviors already in use, which is the main advantage of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

A Methodology to Designing Strategies for Robot Soccer Based on Discrete Event Systems Formalism

Cardoso

Molina

Freire

et al. 2012

2012 Brazilian Robotics Symposium and Latin American Robotics Symposium

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“…Dynamic role switching and formation control are crucial for a successful game [20]. The entire game can be divided into a number of partial tasks [11,24] (evaluation of visual information, image processing, hardware and software implementation of distributed control system, hard-wired or wireless data transmission, information processing, strategy planning and controlling of robots).…”

Section: Introductionmentioning

confidence: 99%

Strategy Description and Modelling for Multi-Agent Systems

Snášel

Martinovič

Kožusznik

2008

2008 7th Computer Information Systems and Industrial Management Applications

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The field of robot soccer provides numerous opportunities for the application of AI methods for game strategy development. Robot soccer is a part of standard applications of distributed system control in real time. The software part of a distributed control system is realized by decision making and executive agents. The algorithm of agents' cooperation was proposed with the control agent on a higher level. The algorithms for agents realized in robots are the same. Real-time dynamic simple strategy description and strategy learning possibility based on game observation is important for discovering opponents strategies and searching for tactical group movements, simulation and synthesis of suitable counter-strategies. For the improvement of game strategy, we are developing an abstract description of the game and propose ways to use this description (e.g. for learning rules and adapting team strategies to every single opponent).

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“…[1][2][3][4][5][6] Another aspect of the problem is the spatial uncertainty that can affect the planning result in robot motion. For a practical mobile robot, one of the most challenging issues is to develop a flexible motion planning algorithm that is adaptable to a dynamically varying working environment and, in the meantime, requires low computational cost.…”

Section: Introductionmentioning

confidence: 99%

A vector-format fuzzy logic approach for online robot motion planning in 3D space and its application to underwater robotic vehicle

Tang

et al. 2006

Robotica

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Due to its inherent advantages such as reasoning in the format of heuristic rules based on human experience and less stringent requirement on environmental description, fuzzy logic is a promising tool for the robot motion planning in 3-dimensional dynamic environment. In general, in the Cartesian space, the variables used in characterizing the motion of a mobile robot, such as position, velocity, and force relative to other objects or coordinate frames, contain both the magnitude and the pointing information. In previous studies, the fuzzy reasoning on the pointing information was often developed based on the decomposition of the pointing vector followed by conventional fuzzy logic technique on individual vector components. Consequently, when multiple pointing variables are involved, the number of fuzzy variables that need to be considered simultaneously becomes large and the rule base may become very complex, which diminishes the advantages of the fuzzy reasoning approach. In this research, we tackle this issue by implementing a new fuzzy reasoning approach based on vector-format fuzzy variables. To achieve this, a set of new membership functions is defined for the vector-format fuzzy variables, followed by the establishment of a series of new vector-based fuzzification, fuzzy inference, and defuzzification procedures. By treating the multidimensional variables as unitary linguistic variables, the number of fuzzy variables in the fuzzy propositions and therefore the scale of the rule base can be reduced considerably. As an application example, the proposed new fuzzy reasoning approach for motion planning is applied to an Underwater Robotics Vehicle (URV) operating in an oceanic environment, where the pointing of the goal and the pointing vectors of the obstacles are treated as vector-type fuzzy variables, which leads to a compact and significantly simplified rule base. The motion planner can successfully guide the URV to move in the complicated dynamic environment in a real-time fashion, which clearly demonstrates the effectiveness and robustness of the new fuzzy logic approach.

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Strategy for collaboration in robot soccer

Cited by 26 publications

References 3 publications

A Methodology to Designing Strategies for Robot Soccer Based on Discrete Event Systems Formalism

A Methodology to Designing Strategies for Robot Soccer Based on Discrete Event Systems Formalism

Strategy Description and Modelling for Multi-Agent Systems

A vector-format fuzzy logic approach for online robot motion planning in 3D space and its application to underwater robotic vehicle

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