E i n d h o v e n

Recent Publications

  • 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. 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, 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.
  • Houtman, W. (TU/e), Kengen, C.M. (TU/e), van Lith, P.H.E.M. (TU/e), ten Berge, R.H.J. (TU/e), Kon, J.J. (TU/e), Meessen, K.J. (TU/e), ... van de Molengraft, R. (TU/e) (2019). Tech United Middle Size League Winner 2019. In RoboCup 2019: Robot World Cup XX (pp.517-528). (Lecture Notes in Computer Science; Volume 11531 LNAI, 2019). Springer. Abstract - After the sequence of winning the RoboCup Middle-Size League (MSL) in even years only (2012, 2014, 2016, 2018), Tech United Eindhoven achieved its first RoboCup win during an odd year at RoboCup 2019. This paper presents an evaluation of the tournament and describes the most notable scientific improvements made in preparation of the tournament. These developments consist of our solution to (unforeseen) localisation problems and the improvements in the control architecture of our eight-wheeled robot. The progress in the shooting lever is elaborated as well as the advancements in the arbitrary ball-detection in order to improve our scoring during the Technical Challenge. Additionally, research towards the application of artificial intelligence in predicting the actions of opponents and recognizing the appearance of the opponent robots will be presented.
  • Kon, J. (TU/e), Houtman, W. (TU/e), Kuijpers, W. (TU/e), & van de Molengraft, R. (TU/e) (2018). Pose and Velocity Estimation for Soccer Robots. Student Undergraduate Research E-Journal!, 4. Abstract - This paper details the design and real-time implementation of a planar state estimator for soccer robots. A camera system, encoders, gyroscope and accelerometer are combined in a two-stage Kalman filter through a constant acceleration model. Inflating Noise Variance is employed to handle slip and ensure convergence in stationary periods. The approach oers substantial improvement w.r.t. the old pose estimator.
  • de Koning L. (TU/e), Mendoza J.P. (CMU), Veloso M. (CMU), van de Molengraft R. (TU/e) (2018) Skills, Tactics and Plays for Distributed Multi-robot Control in Adversarial Environments. In: Akiyama H., Obst O., Sammut C., Tonidandel F. (eds) RoboCup 2017: Robot World Cup XXI. RoboCup 2017. Lecture Notes in Computer Science, vol 11175. Springer, Cham. Abstract - This work presents a pioneering collaboration between two robot soccer teams from different RoboCup leagues, the Small Size League (SSL) and the Middle Size League (MSL). In the SSL, research is focused on fast-paced and advanced team play for a centrally-controlled multirobot team. MSL, on the other hand, focuses on controlling a distributed multi-robot team. The goal of cooperation between these two leagues is to apply teamwork techniques from the SSL, which have been researched and improved for years, in the MSL. In particular, the Skills Tactics and Plays (STP) team coordination architecture, developed for centralized multi-robot team, is studied and integrated into the distributed team in order to improve the level of team play. The STP architecture enables more sophisticated team play in the MSL team by providing a framework for team strategy adaptation as a function of the state of the game. Voting-based approaches are proposed to overcome the challenge of adapting the STP architecture to a distributed system. Empirical evaluation of STP in the MSL team shows a significant improvement in offensive game play when distinguishing several offensive game states and applying appropriate offensive plays.