Publications

• Kempers, S.T. et al. (2025). Tech United Eindhoven Middle Size Leauge Winner 2024. In: Barros, E., Hanna, J. P., Okada, H., Torta, E. (eds) RoboCup 2024: Robot World Cup XXVII. RoboCup 2024. Lecture Notes in Computer Science(), vol 15570. Springer, Cham. Abstract - The RoboCup Middle Size League (MSL) is designed to advance robotics research through autonomous soccer played by robots. In this league, two teams of five robots compete on a field measuring 22 by 14 meters. Research in the MSL focuses on distributed multi-agent systems with robots that rely solely on on-board sensors. At RoboCup 2024, held in Eindhoven, The Netherlands, the Tech United Eindhoven team from Eindhoven University of Technology claimed victory in the MSL competition, which felt particularly special as the tournament took place in their hometown. This article reflects on the tournament and the key developments that contributed to Tech United’s success. We highlight three main areas of progress. Firstly, we showcase a new trajectory planner based on a setpoint generator, which leads to more dynamic and more robust path planning. Secondly, we elaborate on the developments of Tech United towards implementing artificial intelligence for ball and obstacle detection. Finally, we present the progress made in using quadruped robots for the MSL.

• Beumer, R.M. et al. (2024). Tech United Eindhoven Middle Size League Winner 2023. In: Buche, C., Rossi, A., Simões, M., Visser, U. (eds) RoboCup 2023: Robot World Cup XXVI. RoboCup 2023. Lecture Notes in Computer Science(), vol 14140. Springer, Cham. https://doi.org/10.1007/978-3-031-55015-7_36. Abstract - The RoboCup Middle Size League (MSL) aims to promote robotics research through robots playing autonomous soccer. In this league, robots play 5 vs 5 on a field of 22 by 14 m. The research in the MSL focuses on distributed multi-agent systems that exclusively have on-board sensors. At RoboCup 2023 in Bordeaux, France, Tech United Eindhoven of the Eindhoven University of Technology won the MSL competition. This paper reflects on the tournament and the developments that led to the victory of Tech United. Specifically, we discuss three developments. Firstly, the concept of a ‘sweeper keeper’, where the goalkeeper more actively participates in the match, is applied to robotic soccer. Secondly, the developments of Tech United towards a human dribble, where the robots release the ball from the ball handling mechanism during dribbling to gain a higher speed and more freedom of movement, are discussed. Finally, the evolution of using the Skills, Tactics and Plays (STP) framework in MSL is presented.
• Kempers, S.T. et al. (2023). Tech United Eindhoven Middle Size League Winner 2022. In: Eguchi, A., Lau, N., Paetzel-Prüsmann, M., Wanichanon, T. (eds) RoboCup 2022:. RoboCup 2022. Lecture Notes in Computer Science(), vol 13561. Springer, Cham. https://doi.org/10.1007/978-3-031-28469-4_28  . Abstract - During the RoboCup 2022 tournament in Bangkok, Thailand, Tech United Eindhoven achieved the first place in the Middle Size League. This paper presents the work done leading up to the tournament. It elaborates on the new swerve drive platform (winner of the technical challenge) and the progress of making the strategy software more semantic (runner-up of the scientific challenge). Additionally, the implementations of the automatic substitution and of more dynamic passes are described. These developments have led to Tech United winning the RoboCup 2022 tournament, and will hopefully lead to more successful tournaments in the future.
• Olthuis, J. J. (TU/e), van der Meer, N. B. (TU/e), Kempers, S.T. (TU/e), van Hoof, C.A. (TU/e), Beumer, R.M. (TU/e), Kuijpers, W. J. P. (TU/e), Kokkelmans, A.A. (TU/e), Houtman, W. (TU/e), van Eijck, J. J. F. J. (TU/e), Kon, J.J. (TU/e), Peijnenburg, A. T. A. (TU/e), van de Molengraft, M. J. G. (TU/e) (2022). Vision-Based Machine Learning in Robot Soccer. 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_27. Abstract - Robots need to perceive their environment in order to properly interact with it. In the RoboCup Soccer Middle Size League (MSL) this happens primarily through cameras mounted on the robots. Machine Learning can be used to extract relevant features from camera imagery. The real-time analysis of camera data is a challenge for both traditional and Machine Learning algorithms, since all computations in the MSL have to be performed on the robot itself.This contribution shows that it is possible to process camera imagery in real-time using Machine Learning. It does this by presenting the current state of Machine Learning in MSL and providing two examples that won the Scientific and Technical Challenges at RoboCup 2021. Both examples focus on semantic detection of objects and humans in imagery. The Scientific Challenge winner presents how YOLOv5 can be used for object detection in the MSL. The Technical Challenge winner demonstrates how to improve interaction between robots and humans in soccer using OpenPose. This contributes towards the goal of RoboCup to arrive at robots that can beat the human soccer world champion by 2050.
• Houtman, W. (TU/e), Lopez Martinez, C.A. (TU/e & Nobleo Projects), Wang, S. (Reboocon Bionics B.V.), Ketels, A. (Speciaal Machinefabriek Ketels V.O.F.), Bruyninckx, H.P.J. (TU/e & KU Leuven), van de Molengraft, M.J.G. (TU/e) (2021). Dynamic control of steerable wheeled mobile platforms applied to an eight-wheeled RoboCup Middle Size League soccer robot. In Mechatronics, Volume 80, 2021,102693, ISSN 0957-4158, https://doi.org/10.1016/j.mechatronics.2021.102693. Abstract - In the RoboCup Middle Size League two teams of mobile robots play soccer against each other. During the game, agility, i.e. the ability to quickly change the direction of platform movements, is important to react or anticipate fast on the intention of opponents to efficiently perform maneuvers like ball shielding and interception. Therefore, high accelerations are desired which ideally would ask all wheels to contribute to traction in the target direction. However none of the current omnidirectional wheel-based robots in the league offers such a feature. Each pair of wheels can rotate independently about its suspension axis . The new configuration brings new challenges in control: the platform becomes kinematically nonholonomic due to the kinematic constraints around the pivot axes, but it is shown that in the context of the driving task the controller can keep the wheel configurations such that they can generate a force and torque in the directions needed by the task. Hereby, the restriction to minimize the position-error in its three degrees of freedom with respect to a predefined trajectory is relaxed by taking only the degrees of freedom relevant for the task into consideration. A cascaded control strategy is proposed that combines kinematic and dynamic control and also addresses the control-allocation problem. Compared to a full kinematic approach as typically applied on steerable wheeled systems, 2.3 times higher translational and 1.8 times higher angular velocity are demonstrated. For the translational acceleration and angular acceleration, improvement factors of 2.7 and 3.2 are achieved, respectively. The platform made a successful debut during the RoboCup Portuguese Open 2019, showing the robustness of the proposed approach.