Relevant bibliographies by topics / Robot Soccer

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Robot Soccer'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2023

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Journal articles on the topic "Robot Soccer"

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Khamdi, Nur, Mochamad Susantok, and Antony Darmawan. "Technique of Standing Up From Prone Position of a Soccer Robot." EMITTER International Journal of Engineering Technology 6, no. 1 (July 10, 2018): 124–36. http://dx.doi.org/10.24003/emitter.v6i1.300.

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One of the humanoid robots being developed in the field of sports is a soccer robot. A soccer robot is a humanoid robot that can perform activities such as playing football. And a variety method fall down of robot soccer such: falling down toward the front direction, side direction, and rear direction. This paper describes the most stands up methods of a soccer robot from its prone position. The proposed method requires only limited movement with degrees of freedom. The movement standing-up of soccer robot has been implemented on the real robot. Tests we performed showed that reliable standing-up from prone position is possible after a fall and such recovery procedures greatly improve the overall robustness of a Soccer Robot.
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Liu, Jing-Sin, Tzu-Chen Liang, and Yi-An Lin. "Realization of a ball passing strategy for a robot soccer game: a case study of integrated planning and control." Robotica 22, no. 3 (May 2004): 329–38. http://dx.doi.org/10.1017/s0263574703005654.

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Ball passing is an elementary and frequently employed human soccer skill. This paper examines the realization and visualization of ball passing, a low level move-to-ball behavior of a soccer robot, in a robot soccer game. A case study of three mechanically identical mobile robots with a formation ready to pass a ball cyclically in a zigzag pattern is examined. We build a control command driven mobile robot motion simulator with a controller and dynamics of mobile robots, not only nonholonomic kinematic constraints to simulate the motion of a soccer robot driven by wheels torques to generate wheels accelerations, to update the robot position and orientation at successive time instants. Kick motion follows a physical law, and a simplified collision check and response model is utilized for the efficient detection of the hitting a robot with the ball or other robots. The realization of specific ball passing strategy to drive each soccer robot in a position to receive a pass includes three levels of organization, coordination, and execution: careful integrated design of a dynamic formation and role change scheme, ball position estimation, and coordinated trajectory (i.e. path and velocity) planning and tracking control. Simulations are performed to illustrate the feasibility of the realization of ball passing among three robots, implemented by a software program for coordinated trajectory planning and tracking control in the developed simulator.
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Sammut, Claude. "Robot soccer." Wiley Interdisciplinary Reviews: Cognitive Science 1, no. 6 (July 27, 2010): 824–33. http://dx.doi.org/10.1002/wcs.86.

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Wang, Yu Feng, Li Di Wang, and Ting Zhe Zhou. "The Design of FIRA Based on the Dynamic Role Assignment Strategy." Applied Mechanics and Materials 143-144 (December 2011): 274–78. http://dx.doi.org/10.4028/www.scientific.net/amm.143-144.274.

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Robot Soccer provides a good experimental platform for the automatic control, artificial intelligence, robotics and other researches. A soccer robot system is also a typical multi-agent systems(MAS). Every robot in a soccer team is an agent,so the collaboration between agents, the rational apportionment of the robots' roles and the capacity for actions of the robots is the key to winning game. We present a strategy which is based on dynamic programming algorithm and genetic algorithm. Every robot has fitness to each role through which to carry out the dynamic role assignment, meanwhile, the parameters of the fitness functions could be optimized by genetic algorithm.
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Xi-Bao Wu, Xi-Bao Wu, Si-Chuan Lv Xi-Bao Wu, Xiao-Hao Wang Si-Chuan Lv, Tian-Xu Tong Xiao-Hao Wang, Zhuo Tang Tian-Xu Tong, Yi-Qun Wang Zhuo Tang, and Wen-bai Chen Yi-Qun Wang. "Action Design of Lobbing Ball for Humanoid Robot Soccer." 電腦學刊 32, no. 5 (October 2021): 210–21. http://dx.doi.org/10.53106/199115992021103205018.

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Robot soccer is a classic research direction in the field of robotics. From the appearance of soccer robot, it is mainly divided into wheeled robot and humanoid robot. At present, humanoid robots and small group wheeled robots mainly compete on two-dimensional plane. Because of the small competitive dimension, the offensive and defensive tactics tend to be simple. In order to enhance the competitiveness and appreciation of humanoid. And complex motion devices based on human motion capture data (HMCD) are designed Human simulation has gradually become one of the effective means of robot design. In order to enhance the competitiveness and appreciation of humanoid, this paper innovatively designs a set of consistent kicking actions based on darwin-op2 robot, combined with HMCD method, realizes the effect of actively lobbing ball. Ideally, the robot can basically kick the ball above 35cm. Besides the robot can basically kick the ball above 30cm in practice, and the success rate is as high as 75%. It improves the competitiveness from two-dimensional to three-dimensional, which provides new ideas and schemes for attack and defense tactics and expands the dimension of competition. It also provides a new direction for the development of humanoid robot football in the future.
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Bachtiar, Mochamad Mobed, Fadl Lul Hakim Ihsan, Iwan Kurnianto Wibowo, and Risky Eka Wibowo. "Intercept Algorithm for Predicting the Position of Passing the Ball on Robot Soccer ERSOW." Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi 6, no. 1 (January 31, 2021): 35–39. http://dx.doi.org/10.25139/inform.v6i1.3353.

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ERSOW is the name of a wheeled soccer robot that competes in the Kontes Robot Sepak Bola Indonesia (KRSBI). The soccer robot plays a soccer game based on the rules adapted from the human soccer game. The ERSOW team was formed in 2016. Starting in 2017, ERSOW participated in the KRSBI with the Middle Size League (MSL) type. Research in the field of wheeled soccer robots is mostly carried out on robot intelligence, such as how robots detect and look for balls, dribble, pass the ball, avoid opponents, and communicate in teams. This research focuses on the ability that the robot can pass the ball in KRSBI 2020. There are adjustments to the rules for its implementation online where the robot has to pass the ball and score as many goals as possible. The robot's ability to know the direction of ball movement and cut the ball movement or intercept is needed. By utilizing data processing from vision to obtain ball speed data and speed algorithm calculations, the passing ball method has a small chance of missing. Based on the results of experiments that have been carried out, the success of ERSOW in passing using this method is 94.7%.
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Bachtiar, Mochamad Mobed, Iwan Kurnianto Wibowo, and Rakasiwi Bangun Hamarsudi. "Goalpost Detection Using Omnidirectional Cameras on ERSOW Soccer Robots." Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi 5, no. 2 (August 1, 2020): 86–91. http://dx.doi.org/10.25139/inform.v5i2.2744.

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The ERSOW robot is a soccer robot developed by Politeknik Elektronika Negeri Surabaya, Indonesia. One important ability of a soccer robot is the ability to find the goal in the field. Goal Post is often used as a sign by soccer robots in a match. The mark is a reference robot in the field to be used in determining the strategy. By knowing the location of the goal in a field, the soccer robot can make the decision to maneuver in the match to get the right goal kick. There are various methods of detecting goal. One of them is to detect goal post using vision. In this study the radial search lines method is used to detect the goalposts as markers. Image input is generated from an omnidirectional camera. The goal area that is detected is the front side of the goal area. With experiments from 10 robot position points in the field, only 1 position point cannot detect the goal. The robot cannot detect the goal because what is seen from the camera is the side of the goal, so the front side of the goal area is not visible.Keywords— omnidirectional camera, vision, radial search lines, goal detection, ersow soccer robot
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Xiong, Xiaowei. "Artificial Intelligence Control Algorithm for the Steering Motion of Wheeled Soccer Robot." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 10 (September 2019): 1959034. http://dx.doi.org/10.1142/s0218001419590341.

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In this paper, the artificial intelligence control algorithm for steering robot of steering wheel is studied. The steering movement of wheeled soccer robot is controlled by artificial intelligence control algorithm, and the steering movement is modeled and simulated. Firstly, the characteristics of artificial neurons are simulated and a similar control model is constructed to complete the simulation of football. The artificial intelligence control algorithm has a dynamic feedback item compared with the traditional intelligent model, which has a better effect on the steering control of the wheeled soccer robot. In this paper, artificial intelligence control algorithm is used to optimize the parameters of artificial intelligence control algorithm, and the output of control signal of each steering part of wheeled soccer robot is simulated in the experiment, and the control of the steering action of wheeled soccer robot by artificial intelligence control algorithm is verified by experiments. Then the artificial intelligence control algorithm forms the connection structure. This method provides a good reference for steering control of wheeled soccer robots.
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Susanto, Susanto, Taufiq Tegar Pratama, and Riska Analia. "Real-time Coordinate Estimation for Self-Localization of the Humanoid Robot Soccer BarelangFC." JURNAL INTEGRASI 14, no. 2 (October 31, 2022): 81–91. http://dx.doi.org/10.30871/ji.v14i2.4110.

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In implementation, of the humanoid robot soccer consists of more than three robots when played soccer on the field. All the robots needed to be played the soccer as human done such as seeking, chasing, dribbling and kicking the ball. To do all of these commands, it is required a real-time localization system so that each robot will understand not only the robot position itself but also the other robots and even the object on the field’s environment. However, in real-time implementation and due to the limited ability of the robot computation, it is necessary to determine a method which has fast computation and able to save much memory. Therefore, in this paper we presented a real-time localization implementation method using the odometry and Monte Carlo Localization (MCL) method. In order to verify the performance of this method, some experiment has been carried out in real-time application. From the experimental result, the proposed method able to estimate the coordinate of each robot position in X and Y position on the field.
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Wang, Yin-Tien, Zhi-Jun You, and Chia-Hsing Chen. "AIN-Based Action Selection Mechanism for Soccer Robot Systems." Journal of Control Science and Engineering 2009 (2009): 1–10. http://dx.doi.org/10.1155/2009/896310.

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Role and action selections are two major procedures of the game strategy for multiple robots playing the soccer game. In role-select procedure, a formation is planned for the soccer team, and a role is assigned to each individual robot. In action-select procedure, each robot executes an action provided by an action selection mechanism to fulfill its role playing. The role-select procedure was often designed efficiently by using the geometry approach. However, the action-select procedure developed based on geometry approach will become a very complex task. In this paper, a novel action-select algorithm for soccer robots is proposed by using the concepts of artificial immune network (AIN). This AIN-based action-select provides an efficient and robust algorithm for robot role selection. Meanwhile, a reinforcement learning mechanism is applied in the proposed algorithm to enhance the response of the adaptive immune system. Simulation and experiment are carried out to verify the proposed AIN-based algorithm, and the results show that the proposed algorithm provides an efficient and applicable algorithm for mobile robots to play soccer game.
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Dissertations / Theses on the topic "Robot Soccer"

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Graf, Birgit. "Robot soccer." [S.l.] : Universität Stuttgart , Fakultät Informatik, 1999. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB7987414.

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Holen, Vidar, and Audun Marøy. "Learning robot soccer with UCT." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9709.

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Upper Confidence bounds applied to Trees, or UCT, has shown promise for reinforcement learning problems in different kinds of games, but most of the work has been on turn based games and single agent scenarios. In this project we test the feasibility of using UCT in an action-filled multi-agent environment, namely the RoboCup simulated soccer league. Through a series of experiments we test both low level and high level approaches. We were forced to conclude that low level approaches are infeasible, and that while high level learning is possible, cooperative multi-agent planning did not emerge.

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Kelsey, Jed M. "AUTONOMOUS SOCCER-PLAYING ROBOTS: A SENIOR DESIGN PROJECT." International Foundation for Telemetering, 1999. http://hdl.handle.net/10150/608518.

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International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada
This paper describes the experiences and final design of one team in a senior design competition to build a soccer-playing robot. Each robot was required to operate autonomously under the remote control of a dedicated host computer via a wireless link. Each team designed and constructed a robot and wrote its control software. Certain components were made available to all teams. These components included wireless transmitters and receivers, microcontrollers, overhead cameras, image processing boards, and desktop computers. This paper describes the team’s hardware and software designs, problems they encountered, and lessons learned.
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Johnson, Walter H., and Rob Franklin. "Effective Ball Handling and Control in Robot Soccer." International Foundation for Telemetering, 2002. http://hdl.handle.net/10150/606386.

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International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California
An autonomous soccer-playing robot was designed and constructed as part of the electrical engineering senior project at Brigham Young University. Unique physical features enable ball handling abilities. A front-side rotating drum retains the ball by applying backspin. A pneumatic kicker allows for fast accurate kicks. Robot movement control is performed by three different systems. The low-level velocity controller ensures output of desired forward and angular velocities. The position controller is used to match the robot's position with a desired position. Path generation directs the robot along a desired path at a specified velocity. The locations of the robots and ball on the soccer field is determined by the vision system. This document is a formal description of the unique designs and construction of the our team's robot.
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Lei, Wai Ip. "A multi agents control approach to robot soccer competition." Thesis, University of Macau, 2004. http://umaclib3.umac.mo/record=b1446190.

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Zhao, Hong Bin. "Real time control strategy towards the robot soccer system." Thesis, University of Macau, 2002. http://umaclib3.umac.mo/record=b1447842.

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Thomas, Peter James, and p. thomas@cqu edu au. "Evolutionary Learning of Control and Strategies in Robot Soccer." Central Queensland University. School of Advanced Technologies and Processes, 2003. http://library-resources.cqu.edu.au./thesis/adt-QCQU/public/adt-QCQU20040628.153250.

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Robot soccer provides a fertile environment for the development of artificial intelligence techniques. Robot controls require high speed lower level reactive layers as well as higher level deliberative functions. This thesis focuses on a number of aspects in the robot soccer arena. Topics covered include boundary avoidance strategies, vision detection and the application of evolutionary learning to find fuzzy controllers for the control of mobile robot. A three input, two output controller using two angles and a distance as the input and producing two wheel velocity outputs, was developed using evolutionary learning. Current wheel velocities were excluded from the input. The controller produced was a coarse control permitting only either forward or reverse facing impact with the ball. A five input controller was developed which expanded upon the three input model by including the current wheel velocities as inputs. The controller allowed both forward and reverse facing impacts with the ball. A five input hierarchical three layer model was developed to reduce the number of rules to be learnt by an evolutionary algorithm. Its performance was the same as the five input model. Fuzzy clustering of evolved paths was limited by the information available from the paths. The information was sparse in many areas and did not produce a controller that could be used to control the robots. Research was also conducted on the derivation of simple obstacle avoidance strategies for robot soccer. A new decision region method for colour detection in the UV colour map to enable better detection of the robots using an overhead vision system. Experimental observations are given.
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Olson, Steven A. R., Chad S. Dawson, and Jared Jacobson. "DESIGN AND DEVELOPMENT OF AN AUTONOMOUS SOCCER-PLAYING ROBOT." International Foundation for Telemetering, 2002. http://hdl.handle.net/10150/607517.

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International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California
This paper describes the construction of an autonomous soccer playing robot as part of a senior design project at Brigham Young University. Each participating team designed and built a robot to compete in an annual tournament. To accomplish this, each team had access to images received from a camera placed above a soccer field. The creation of image processing and artificial intelligence software were required to allow the robot to perform against other robots in a one-on-one competition. Each participating team was given resources to accomplish this project. This paper contains a summary of the experiences gained by team members and also a description of the key components created for the robot named Prometheus to compete and win the annual tournament.
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Peel, Andrew Gregory. "On designing a mobile robot for robocup /." Connect to thesis, 2006. http://eprints.unimelb.edu.au/archive/00003101.

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Ros, Espinoza Raquel. "Action Selection in Cooperative Robot Soccer using Case-Based Reasoning." Doctoral thesis, Universitat Autònoma de Barcelona, 2008. http://hdl.handle.net/10803/5783.

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La tasca de dissenyar el mecanisme de presa de decisions d'un equip de robots és un gran repte, no només per la complexitat de l'entorn en el qual els robots realitzen les seves tasques, que comporta incertesa, dinamicitat i imprecisió, sinó també perquè la coordinació entre els robots s'ha de tenir en compte a l'hora de dissenyar el mecanisme. Els robots han de ser conscients de les accions dels altres robots per tal de cooperar i assolir satisfactòriament els objectius de l'equip.
Aquesta tesi doctoral presenta una novedosa aproximació basada en casos per la selecció d'accions i la coordinació de tasques cooperatives en equips de robots. Aquesta aproximació s'ha aplicat i avaluat en un domini molt representatiu, com és el del futbol robòtic, tot i que les idees presentades són aplicables a altres dominis com les operacions de rescat, l'exploració d'entorns desconeguts i la vigilància submarina, entre d'altres.
El procés de selecció proposa un cas per reutilitzar, avaluant els casos candidats amb una sèrie de criteris per tal de tenir en compte les característiques d'un entorn real, incloent-hi la presència d'adversaris, que és un factor clau en el domini del futbol robòtic. A diferència dels sistemes de raonament basats en casos clàssics, la reutilització del cas consisteix en l'execució d'un conjunt d'accions per part d'un equip de robots. Per tant, des de la perspectiva multi- robot, el sistema ha d'incloure un mecanisme per tal de decidir qui fa què i com. En aquesta tesi, es presenta una arquitectura multi-robot juntament amb un mecanisme de coordinació per tal d'atacar aquests reptes.
Hem validat experimentalment l'aproximació tant en simulació com amb robots reals. L'experimentació ha permès comprovar que l'aproximació presentada assoleix els objectius de la tesi, és a dir, el disseny de comportaments d'un equip de robots cooperatius. Així mateix, els resultats obtinguts també mostren els avantatges d'utilitzar una estratègia col·laborativa en entorns en els quals el component adversari juga un paper important, en contrast amb comportaments individualistes.
Designing the decision-making engine of a team of robots is a challenging task, not only due to the complexity of the environment where the robots usually perform their task, which include uncertainty, dynamism and imprecision, but also because the coordination of the team must be included in this design. The robots must be aware of other robots' actions to cooperate and to successfully achieve their common goal. Besides, decisions must be made in real-time and with limited computational resources.
This thesis contributes a novel case-based approach for action selection and coordination in joint multi-robot tasks in real environments. This approach has been applied and evaluated in the representative domain of robot soccer, although the ideas presented are applicable to domains such as disaster rescue operations, exploration of unknown environments and underwater surveillance, among others.
The retrieval process proposes a case to reuse, evaluating the candidate cases through different measures to overcome the real world characteristics, including the adversarial component which is a key ingredient in the robot soccer domain. Unlike classical case- based reasoning engines, the case reuse consists in the execution of a set of actions through a team of robots. Therefore, from the multi- robot perspective, the system has to include a mechanism for deciding who does what and how. In this thesis, we propose a multi- robot architecture along with a coordination mechanism to address these issues.
We have validated the approach experimentally both in a simulated environment and with real robots. The results showed that our approach achieves the expected goals of the thesis, i.e. designing the behavior of a cooperative team of robots. Moreover, the experimentation also showed the advantages of using collaborative strategies in contrast to individualistic ones, where the adversarial component plays an important role.
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Books on the topic "Robot Soccer"

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1961-, Kitano Hiroaki, ed. RoboCup-97: Robot soccer World Cup I. Berlin: Springer, 1998.

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Michael, Mayer N., Savage Jesus, Saranlı Uluc̨, and SpringerLink (Online service), eds. RoboCup 2011: Robot Soccer World Cup XV. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Baltes, Jacky. RoboCup 2009: Robot Soccer World Cup XIII. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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Chen, Xiaoping. RoboCup 2012: Robot Soccer World Cup XVI. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Frank, Dellaert, Ohashi Takeshi, Ribeiro Fernando, Siekmann Jörg H, Visser Ubbo, and SpringerLink (Online service), eds. RoboCup 2007: Robot Soccer World Cup XI. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2008.

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Asada, Minoru, and Hiroaki Kitano, eds. RoboCup-98: Robot Soccer World Cup II. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48422-1.

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Iocchi, Luca, Hitoshi Matsubara, Alfredo Weitzenfeld, and Changjiu Zhou, eds. RoboCup 2008: Robot Soccer World Cup XII. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02921-9.

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Baltes, Jacky, Michail G. Lagoudakis, Tadashi Naruse, and Saeed Shiry Ghidary, eds. RoboCup 2009: Robot Soccer World Cup XIII. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11876-0.

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Röfer, Thomas, N. Michael Mayer, Jesus Savage, and Uluc̨ Saranlı, eds. RoboCup 2011: Robot Soccer World Cup XV. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32060-6.

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Lakemeyer, Gerhard, Elizabeth Sklar, Domenico G. Sorrenti, and Tomoichi Takahashi, eds. RoboCup 2006: Robot Soccer World Cup X. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74024-7.

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Book chapters on the topic "Robot Soccer"

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Bräunl, Thomas. "Robot Soccer." In Embedded Robotics, 259–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05099-6_18.

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Veloso, Manuela M. "Robot Soccer: A Multi-Robot Challenge." In Multi-Robot Systems: From Swarms to Intelligent Automata, 169–74. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-2376-3_18.

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Arenas, Matías, Javier Ruiz-del-Solar, Simón Norambuena, and Sebastián Cubillos. "A Robot Referee for Robot Soccer." In RoboCup 2008: Robot Soccer World Cup XII, 426–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02921-9_37.

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Kim, Jong-Hwan, Yong-Jae Kim, Dong-Han Kim, and Kiam-Tian Seow. "7. Simulated Robot Soccer." In Springer Tracts in Advanced Robotics, 257–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-40921-2_7.

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Shen, Wei-Min, Jafar Adibi, Rogelio Adobbati, Bonghan Cho, Ali Erdem, Hadi Moradi, Behnam Salemi, and Sheila Tejada. "Autonomous soccer robots." In RoboCup-97: Robot Soccer World Cup I, 295–304. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64473-3_68.

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Yetişenler, Çağdaş, and Ahmet Özkurt. "Multiple Robot Path Planning for Robot Soccer." In Artificial Intelligence and Neural Networks, 11–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11803089_2.

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Ciesielski, Vic, Dylan Mawhinney, and Peter Wilson. "Genetic Programming for Robot Soccer." In RoboCup 2001: Robot Soccer World Cup V, 319–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45603-1_37.

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Larik, Asma S., and Sajjad Haider. "Opponent Classification in Robot Soccer." In Current Approaches in Applied Artificial Intelligence, 478–87. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19066-2_46.

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Lund, Henrik Hautop, and Luigi Pagliarini. "Robot Soccer with LEGO Mindstorms." In Lecture Notes in Computer Science, 141–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48422-1_11.

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Behnke, Sven, Jürgen Müller, and Michael Schreiber. "Playing Soccer with RoboSapien." In RoboCup 2005: Robot Soccer World Cup IX, 36–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11780519_4.

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Conference papers on the topic "Robot Soccer"

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Passault, Gregoire, Clement Gaspard, and Olivier Ly. "Robot Soccer Kit: Omniwheel Tracked Soccer Robots for Education." In 2022 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2022. http://dx.doi.org/10.1109/icarsc55462.2022.9784808.

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Han, Chin Yun, S. Parasuraman, I. Elamvazhuthi, C. Deisy, S. Padmavathy, and M. K. A. Ahamed khan. "Vision Guided Soccer Robot." In 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). IEEE, 2017. http://dx.doi.org/10.1109/iccic.2017.8524422.

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Byoung-Ju Lee and Gwi-Tae Park. "A robot in intelligent environment: soccer robot." In 1999 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. IEEE, 1999. http://dx.doi.org/10.1109/aim.1999.803145.

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"ROBOT SOCCER STRATEGY – BIOMIMETIC APPROACH." In 7th International Conference on Informatics in Control, Automation and Robotics. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002954004330436.

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Mansoor, Shamyl Bin, Shahid Razzaq, Ahsan Rehman, and Asad Ali Shah. "Robot soccer framework for learning." In 2011 IEEE 14th International Multitopic Conference (INMIC). IEEE, 2011. http://dx.doi.org/10.1109/inmic.2011.6151509.

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Plestina, Vladimir, Hrvoje Turic, and Vladan Papic. "Constructive Education Approach: Robot Soccer." In 2007 29th International Conference on Information Technology Interfaces. IEEE, 2007. http://dx.doi.org/10.1109/iti.2007.4283808.

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Guofeng Tong, Hongsheng He, and Zhenzhou Shao. "A HiFi simulator for Robot Soccer." In 2008 7th World Congress on Intelligent Control and Automation. IEEE, 2008. http://dx.doi.org/10.1109/wcica.2008.4593407.

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Kim, Jinwon, Bongsu Kim, Jinwoo Yoon, Marley Lee, Sunah Jung, and Jae young Choi. "Robot Soccer Using Deep Q Network." In 2018 International Conference on Platform Technology and Service (PlatCon). IEEE, 2018. http://dx.doi.org/10.1109/platcon.2018.8472776.

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Asik, Okan, and H. Levent Akin. "A visual compass for robot soccer." In 2014 22nd Signal Processing and Communications Applications Conference (SIU). IEEE, 2014. http://dx.doi.org/10.1109/siu.2014.6830651.

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Sluzek, A., and P. K. D. Minh. "Embedded Vision Module for Robot-soccer." In IEEE International Conference on Computer Systems and Applications, 2006. IEEE, 2006. http://dx.doi.org/10.1109/aiccsa.2006.205084.

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Reports on the topic "Robot Soccer"

1

Searock, Jeremy, Brett Browning, and Manuela Veloso. Segway CMBalance Robot Soccer Player. Fort Belvoir, VA: Defense Technical Information Center, May 2004. http://dx.doi.org/10.21236/ada461062.

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Tanzman, J. Sensitivity Studies Evaluating the Effects of Geometry Variability on Socket Weld Root Stresses. Office of Scientific and Technical Information (OSTI), February 2000. http://dx.doi.org/10.2172/767339.

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