Abstract
This article aims to present the contributions of the soccer robot project based on RoboCupJunior Soccer Open. The project proposes the 3D modeling of the robot in order to create a virtual version before the physical robot. In the virtual robot, it is implemented the algorithm, are validated the game strategies, and tested the design functionality in the robot structure through the 3D simulation environment. This virtual environment was developed within the parameters of the competition to provide greater consistency and integrity during the simulations, which allows time optimization, project improvement, problem correction and solution implementation before robot construction. The potential of the simulation environment is visible, which can encourage a 3D Simulation modality of Soccer at RoboCupJunior.
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References
RoboCupJunior Soccer - Rules (2020). https://junior.robocup.org/wp-content/uploads/2020Rules/final_2020rules/RCJ2020-Soccer-final.pdf. Accessed 24 Apr 2021
Solidworks. https://www.solidworks.com/. Accessed 24 Apr 2021
Altium. https://www.altium.com/. Accessed 24 Apr 2021
V-Rep. http://www.coppeliarobotics.com/. Accessed 24 Apr 2021. HuangYu-WeiShiao
Huang, S., Shiao, Y.: 2D path control of four omni wheels mobile platform with compass and gyroscope sensors. Sensors Actuators A: Phys. 234, 302–310 (2005)
Magalhães, G., Colombini, L.: Detecção de objetos no futebol de robôs, Campinas-SP, Brazil (2017)
Anjum, L., Park, J., Hwang, W.: Sensor data fusion using unscented Kalman filter for accurate localization of mobile robots. In: IEEE International Conference on Control, Automation and Systems, pp. 947–952 (2010)
Li, Q., et al.: Accurate, fast fall detection using gyroscopes and accelerometer-derived posture information. In: IEEE Sixth International Workshop on Wearable and Implantable Body Sensor Networks, pp. 138–143 (2009)
Mujahed, M., Mertsching, B.: The admissible gap (AG) method for reactive collision avoidance. In: IEEE International Conference on Robotics and Automation, ICRA, pp. 1916–1921 (2017)
Marco, A., et al.: Virtual vs. real: trading off simulations and physical experiments in reinforcement learning with Bayesian optimization. In: IEEE International Conference on Robotics and Automation, ICRA, pp. 1557–1563 (2017)
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Queiroz, B.C., Ferreira, F. (2022). Soccer Robots Modeling Project Based on RoboCupJunior: Simulation Environment for Physical Robot Improvement. In: Alami, R., Biswas, J., Cakmak, M., Obst, O. (eds) RoboCup 2021: Robot World Cup XXIV. RoboCup 2021. Lecture Notes in Computer Science(), vol 13132. Springer, Cham. https://doi.org/10.1007/978-3-030-98682-7_10
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DOI: https://doi.org/10.1007/978-3-030-98682-7_10
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