Robot Soccer Control Using Behaviour Trees and Fuzzy Logic

Abiyev, Rahib H.; Günsel, Irfan; Akkaya, Nurullah; Aytac, Ersin; Çağman, Ahmet; Abizada, Sanan

doi:10.1016/j.procs.2016.09.430

Cited by 29 publications

(10 citation statements)

References 22 publications

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“…Human-Aware Navigation Component Cognitive Architecture task planning in robotics as a replacement for finite state machines (FSM) [2]. The use of BTs simplifies the decision-making process [1].…”

Section: Navigation2mentioning

confidence: 99%

Impact of decision-making system in social navigation

Clavero

Rico

Rodríguez-Lera

et al. 2022

Multimed Tools Appl

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Facing human activity-aware navigation with a cognitive architecture raises several difficulties integrating the components and orchestrating behaviors and skills to perform social tasks. In a real-world scenario, the navigation system should not only consider individuals like obstacles. It is necessary to offer particular and dynamic people representation to enhance the HRI experience. The robot’s behaviors must be modified by humans, directly or indirectly. In this paper, we integrate our human representation framework in a cognitive architecture to allow that people who interact with the robot could modify its behavior, not only with the interaction but also with their culture or the social context. The human representation framework represents and distributes the proxemic zones’ information in a standard way, through a cost map. We have evaluated the influence of the decision-making system in human-aware navigation and how a local planner may be decisive in this navigation. The material developed during this research can be found in a public repository (https://github.com/IntelligentRoboticsLabs/social_navigation2_WAF) and instructions to facilitate the reproducibility of the results.

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Section: Navigation2mentioning

confidence: 99%

Impact of decision-making system in social navigation

Clavero

Rico

Rodríguez-Lera

et al. 2022

Multimed Tools Appl

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“…While in the paper [33], it can be seen that there were design and implementation of the fuzzy hybrid architecture for intelligent navigation systems and mobile robot control in avoiding obstacles in static and dynamic environments. Just as in the case of robot football, fuzzy logic is very important, applied to individual robot behaviors and actions, especially for obstacle avoidance and achieving targets [34] [35].…”

Section: Using Type 1 Fuzzy Logic Controllermentioning

confidence: 99%

Application of Type-1 and Type-2 Fuzzy Logic Controller for The Real Swarm Robot

et al. 2019

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Navigation is one of the typical problem domains occurred in studying swarm robot. This task needs a special ability in avoiding obstacles. This research presents the navigation techniques using type 1 fuzzy logic and interval type 2 fuzzy logic. A comparison of those two fuzzy logic performances in controlling swarm robot as tools for complex problem modeling, especially for path navigation is presented in this paper. Each hierarchical of fuzzy logic shows its advantages and disadvantages. For testing the robustness of type-1 fuzzy logic and interval type-2 fuzzy logic algorithms, 3 robots for the real swarm robot experiment are used. Each is equipped with one compass sensor, three distance sensors, and one X-Bee communication module. The experimental results show that type-2 fuzzy logic has better performance than type-1 fuzzy logic.

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“…Considerable research in navigating a mobile robot in an uncertain environment has been conducted. One of the developed controllers is soft computing, such as Fuzzy Logic Controller [21]- [29]. The improvement in computational method enables to design a controller based on designed robot's behavior without going through a specified complex model of the robot and the world.…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

An Fuzzy Logic Simulation As a Teaching-Learning Media for Artificial Intelligence Class

Dewi¹,

Risma²,

Oktarina³

2018

JAMRIS

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�olytechnic as a �oca�onal educa�on ins�tu�on has to �eep upda�ng its curriculum with inno�a�on and the latest technology applica�on in industry and domes�c. Teaching learning process in the classroom also has to be based on technology applica�on. The teachinglearning process will be more e�ec��e and interes�ng by in�ol�ing the students to be more pro-ac��e and crea��e. To engage the students more, the teacher needs a teaching-learning media, and one of these media is simula�on so�ware. The �isualiza�on of the simula�on a�racts students� interest and enhances students� crea��ity. This paper proposes the applica�on of an open source and low-cost so�ware simula�on as a teaching-learning media to create an interac��e and e�ci�ng robo�cs class. This study will show the design and applica�on of fuzzy logic controller in a mobile firefighter robot, and simulate the design in SCILAB, an open source so�ware, and in �obotSim, a low-cost so�ware. This alterna��e of open source so�ware can be as good as the high-end ones. This paper shows that the applica�on of fuzzy logic controller can be fun and �ariant for students to en�oy the class. The contribu�on of this research is to show and encourage teachers and students to learn robo�cs and ar�ficial intelligence in an interac��e classroom using free so�ware and also encourage them to search more alterna��e open source so�ware.

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Robot Soccer Control Using Behaviour Trees and Fuzzy Logic

Cited by 29 publications

References 22 publications

Impact of decision-making system in social navigation

Impact of decision-making system in social navigation

Application of Type-1 and Type-2 Fuzzy Logic Controller for The Real Swarm Robot

An Fuzzy Logic Simulation As a Teaching-Learning Media for Artificial Intelligence Class

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