A COORDINATION SYSTEM FOR DECISION MAKING ON WHEEL FOOTBALL ROBOT
Keywords:
wheeled soccer robot, coordination system, centralized control, data integration, decision making, dijkstra’s algorithmAbstract
Wheeled robot soccer matches have problems, one of which is the ability to coordinate. Because in a one-wheeled soccer robot match a team consists of several robots, then cohesiveness is the deciding factor to produce a good game. To produce good cohesiveness, coordination between robots is needed. In this final project a coordination system for decision making in a wheeled soccer robot team is designed. This research was conducted by simulating three robot units, one coordinator robot unit and two member robot units, with the addition of 3 silent robot opponents. The main concept of this research is the action taken by each robot in the team is the result of the decision of the coordinating robot. Robot members have two jobs in the team, namely sending all match situation data read by the sensor to the coordinating robot, and executing commands for each robot that is determined by the coordinating robot. The coordinating robot gives commands to each robot based on all match condition data collected by all robots. To avoid other robots in the team when moving, sin and cos rules are used. Meanwhile, to avoid opposing robots as well as path planning using Dijkstra’s Algorithm. The results of this study the robot managed to move in a coordinated manner that is only moving the robot that is most suitable for action. While the other robots are prepared to wait for conditions suitable for him to take action. Besides robots can also move without crashing into other robots both robots in the team and the robot opponent. In various cases carried out in testing, the robot takes from 3 to 5 seconds to do its job.
References
[2] F. A. Rahman et al., “Motion Planning in Dynamic Environment for Middle Size League using Theta* and Polynomial Trajectory Generator,†in 5th Indonesian Symposium on Robotic Systems and Control, 2017, pp. 113–117.
[3] I. P. Suryaningsih, A. Risal, H. Jaya, and A. R. Soccer, “Algoritma Multi Planning Pada Robot Soccer,†5th Indones. Symp. Robot. Syst. Control, pp. 156–159, 2017.
[4] R. H. Abiyev, I. Günsel, N. Akkaya, E. Aytac, A. Çaǧman, and S. Abizada, “Robot Soccer Control Using Behaviour Trees and Fuzzy Logic,†2016, doi: 10.1016/j.procs.2016.09.430.
[5] Fitri, K. R. R, A. Rahmansyah, and W. Darwin, “Penggunaan Bahasa Pemrograman Python Pusat Kendali Pada Robot 10-D,†in 5th Indonesian Symposium on Robotic Systems and Control, 2017, pp. 23–26.
[6] R. A. Pamungkas, A. Maulana, D. P. Sya’ban, R. Ramdani, A. Musafa, and I. Riyanto, “WiFi Data Communication System Design for Wheeled Soccer Robot Controller,†Adv. Sci. Lett., vol. 24, no. 11, pp. 8782–8786, 2018, doi: 10.1166/asl.2018.12345.
[7] M. Occhiogrosso, Graphs of Trigonometric Functions: Trigonometry. Milliken Publishing Company, 2007, 2007.
[8] E. W. Dijkstra, “A note on two problems in connexion with graphs,†Numer. Math., vol. 1, no. 1, pp. 269–271, 1959, doi: 10.1007/BF01386390.
[9] S. A. Fadzli, S. I. Abdulkadir, M. Makhtar, and A. A. Jamal, “Robotic indoor path planning using dijkstra’s algorithm with multi-layer dictionaries,†2015 IEEE 2nd Int. Conf. InformationScience Secur. ICISS 2015, 2016, doi: 10.1109/ICISSEC.2015.7371031.
[10] S. Pietrzik and B. Chandrasekaran, “Setting up and Using ROS-Kinetic and Gazebo for Educational Robotic Projects and Learning,†in Journal of Physics: Conference Series, 2019, vol. 1207, no. 1, doi: 10.1088/1742-6596/1207/1/012019.
[11] N. Koenig and A. Howard, “Design and use paradigms for Gazebo, an open-source multi-robot simulator,†2004 IEEE/RSJ Int. Conf. Intell. Robot. Syst., vol. 3, pp. 2149–2154, 2004, doi: 10.1109/iros.2004.1389727.
[12] lentin joseph, “Robotic Operating System,†Introduction to ROS. p. 385, 2017, [Online]. Available: https://www.ros.org.
