Participating Teams 2021

Teams participating in the Worldwide SPL Competition 2021:

Team Obstacle Avoidance Passing 1vs1 Autonomous Calibration Arena*
Bembelbots (✓)
Berlin United – NaoTH (✓)
B-Human
Dutch Nao Team
HTWK Robots
HULKs
Nao Devils
Naova
NomadZ (✓)
rUNSWift
R-ZWEI KICKERS
SPQR Team
Starkit ?
UT Austin Villa (✓)

* (✓) means a smaller field. A goal area may be present or not. All information without guarantee.



Bembelbots
Germany

Team Contact:
Jens-Michael Siegl

Institutes:
Goethe University Frankfurt am Main

Team Profile: The RoboCup team Bembelbots was founded in 2009 at the Goethe University Frankfurt (Main), Germany as a group fully organized by students. As there is no robotics group at the university, the team should help students to increase their experience in robotics, as well as programming skills in addition to the theoretical orientation of the computer science degree program of the university. For that reason, we started developing our own framework from scratch.
Team Bembelbots has regularly competed in the RoboCup German Open since 2010 as well as the RoboCup Worldcups in 2012, 2013 & 2016-2019. .
Research Topics: Machine Learning, Localization, Behavior Modeling, Software architecture
Team Report: 2019 Team Report


Berlin United – Nao Team Humboldt (BU-NaoTH)
Germany

Team Contact:
Heinrich Mellmann
Benjamin Schlotter

Institutes:
Humboldt-Universität zu Berlin
Adaptive Systems Group

Team Profile: “Berlin United”, formerly Nao Team Humboldt (NaoTH), is part of the Adaptive Systems group at the Humboldt-Universität zu Berlin. Our group has been involved in RoboCup since 1998 with various teams in different leagues. Berlin United was established in 2007 and is participating in SPL since the first competition of the league in 2008 in Suzhou/China. At the last RoboCup in Sydney in 2019 our team won the Technical challenge and the Mixed-Team competition as part of the mixed team “B&B” together with B-Human. At the current state the human part of the team consists of about 6 students of Bachelor, Master/Diploma, and PhD levels as well as several active alumni. Besides the direct participation at the RoboCup competitions Berlin United is actively involved in teaching at the university, public engagement and fostering of the RoboCup community. 

The codebase is fully original and is being progressively developed over the years. The source code is being made open source on an annual basis and can be found at

https://github.com/BerlinUnited/NaoTH

Research Topics: Our research interests span a wide spectrum including software architecture and tools, basic motion control, visual spatial perception, proprioception, state estimation and modeling, high level planning and team coordination. Two of our most recent projects focused on simulation based decision making, and an infrastructure for gathering and evaluation of the data from the RoboCup games on a large scale: http://robocup.tools. The latter project aims to foster data driven research within RoboCup and was supported by RCF League Development grants in 2017, 2018 and 2020.
Team Report: Team Report 2019


B-Human
Germany

Team Contact:
Thomas Röfer, Tim Laue

Institutes:
DFKI Bremen, Cyber-Physical Systems
University of Bremen, Department of Computer Science

Team Profile: B-Human consists of students from the University of Bremen in their advanced study period and researchers from both the University Bremen and the DFKI Bremen. In the past, members of the B-Human team participated in different RoboCup leagues. B-Human won the RoboCup World Championships 2009, 2010, 2011, 2013, 2016, 2017, and 2019. We also won the RoboCup German Open 2009-2017 and 2019, the European Open in 2016, the RoboCup Technical Challenges in 2009, 2013, 2014, 2015, 2017, and 2018, the Drop-in Player competitions at the RoboCup German Open 2014 and 2015 and at the RoboCup 2014 and 2016, and all Mixed Team Competitions of the league. In addition, B-Human team members earned the Best Paper Award at the RoboCup Symposiums 2010 and 2013.
Research Topics: Probabilistic state estimation, real-time computer vision, machine learning, robot simulation, motion control
Team Report: 2019 Team Report and Code Release


Dutch Nao Team
The Netherlands

Team Contact:
Hidde Lekanne gezegd Deprez

Institutes:
Universiteit van Amsterdam, Faculty of Science, Informatics Institute

Team Profile: The Dutch Nao Team consists of bachelor students, master students and alumni, supported by a senior staff-member. The team debuted at the German Open 2010 and made its breakthrough by qualifying for RoboCup Istanbul in 2011. In 2017, the team started its own new framework where each module represents one algorithm handling a task in the football playing robot.
Research Topics: Computer vision, behaviour control, probabilistic robotics, machine learning
Team Report: 2020 Team Report


HTWK Robots
Germany

Team Contact:
Rico Tilgner

Institutes:
Faculty of Computer Science and Media, Leipzig University of Applied Sciences

Team Profile: HTWK Robots (formerly Nao-Team HTWK) is a RoboCup team that consists of graduate and undergraduate students of Leipzig University of Applied Sciences and was founded in 2009. The team participated in RoboCup and RoboCup German Open events from 2009 onwards.
Research Topics: Evolutionary Algorithms, Biped Walking, Artificial Intelligence, Multi-Robot Coordination, Computer Vision, Localization
Team Report: 2019 Team Report


HULKs
Germany

Team Contact:
Patrick Göttsch

Institutes:
Hamburg University of Technology

Team Profile: HULKs is student association of graduate and undergraduate students established in 2013 working in their leisure time or in thesis works on RoboCup SPL topics. We developed an own NAO framework. Team members participated at RoboCup from 2014 to 2018, IranOpen 2017, 2018, GermanOpens in 2014, 2015 and 2017, 2018 and EuropeanOpen in 2016. For 2015, 2017, 2018 and 2019 we were prequalifed for the RoboCup and last year we became fourth at RoboCup. We organize the RoHOW for the last five years.
Research Topics: Fast and reliable software frameworks, biped walking, machine learning, computer vision, path planning
Team Report: 2016, 2017, 2018, 2019


Nao Devils
Germany

Team Contact:
Arne MoosIngmar SchwarzAaron Larisch, Diana Kleingarn

Institutes:
TU Dortmund University

Team Profile: The team consists of researchers and students of TU Dortmund University. We participate in RoboCup competitions since 2002 with several different teams: Microsoft Hellhounds and as part of the German Team (4-Legged-League), DoHBots (Humanoid League), and BreDoBrothers (together with University Bremen) and now as Nao Devils Dortmund in the Standard Platform League.
Research Topics: biped walking, computer vision, stochastic filtering, artificial intelligence, deep learning, reinforcement learning, beam forming
Team Report: 2019 Team Report


Naova ETS
Canada

Team Contact:
Ariane Beaudry-Betournay
Jonathan Fortin

Institutes:
École de Technologie Supérieur

Team Profile: Naova is a relatively young team, with one year experience in the standard platform league (SPL) division and in various other divisions in robotics, and we strive to develop our skills in the SPL division. Composed of 10 engineering students from École de Technologie Supérieure (ÉTS) – Montréal, Québec, Canada. The team consists of a pool of a diversified and talented group of engineering students with various background expertise whom all share the same passion for robotics and its applications. The scientific university club Naova pushes for its members to surpass themselves. By their active involvement in the clubs day-to-day activities , the members get a chance to prove themself which is an opportunity to show their engagement and expertise in a competitive environment. The international competition is a good opportunity for education, advancement and innovation of the members of the club.
Research Topics: Gate generation; deep learning; reinforcement learning; nonlinear control; vision.
Team Report: Not Available

 

NomadZ

Switzerland

Team Contact:
Giuliano Albanese

Institutes:
Department of Information Technology and Electrical Engineering ETH Zurich
Automatic Control Laboratory (IfA)
Computer Vision Laboratory (CVL)

Team Profile: The NomadZ from ETH Zurich, Switzerland, participated for the first time in the RoboCup 2016 Team Competition. The team consists of five to ten graduate students from the Department of Information Technology and Electrical Engineering and the Department of Mechanical and Process Engineering and are supervised by four Ph.D. students. Our work is based on the B-Human code release 2013 and we have implemented modifications and additions in the area of perception, behavior and to a limited extent in motor control.
Research Topics: Automatic calibration, Deep Learning, Kicking, Optimal Game Strategy, Sensor Fusion.
Team Report: Not available


rUNSWift
Australia

Team Contact:
Claude Sammut

Institutes:
UNSW Sydney

Team Profile: rUNSWift is the University of New South Wales team in RoboCup SPL. The team is mostly made up of undergraduate students from Computer Science and Mechatronic Engineering, with some postgraduate and alumni members. Undergraduate students are often enrolled in an Honours thesis or Special Project course as part of their studies. At the international robocup SPL competition, the team won the championship in 2014 and 2015.
Research Topics: Autonomous Systems is a priority research topic in robotics at CSE, UNSW. Our general research focus, of which the RoboCup SPL is a part, is to: 

  • further develop reasoning methods that incorporate uncertainty and real-time constraints and that integrate with the statistical methods used in SLAM and perception
  • develop methods for using estimates of uncertainty to guide future decision making so as to reduce the uncertainty
  • extend these methods for multi-robot cooperation
  • use symbolic representations as the basis for human-robot interaction
  • develop learning algorithms for hybrid systems, such as using knowledge of logical constraints to restrict the search of a trial-and-error learner and learning the constraints
  • develop high level symbolic robotic languages that provide abstractions for a large range of deliberation, planning and learning techniques so as to simplify robot programming
Team Report: 2019 Team Paper


R-ZWEI KICKERS
Germany

Team Contact:
Adrian Müller

Institute:
University of Applied Sciences Kaiserslautern, Department of Computer Sciences and Microsystem Technology

Team Profile: The R-ZWEI KICKERS are part of the Smart Machines working group at UAS Kaiserslautern, located in Zweibrücken, Rhineland-Palatinate. So far, we have remotely participated in the 2021 German Open Replacement Event of the SPL. Our team starts in RoboCup 2021 in two different local challenges. The R-ZWEI KICKERS were established in 2020 and currently consist of one professor and about 10 undergraduate and graduate students in the Department of Computer Science, as well as external volunteers. Currently, our code base is a modified version of the B-Human Code Drop 2019. We have modified team behaviour control and the SimRobot environment to allow for automatic test procedures. Completely custom features include the Teach-In of robot behaviour, a data mining analysis and coupled it to a reinforcement learning (Q-learning) module. Additionally, we have developed our own Image recognition and multi-object detection model.
Research Topics: Machine Learning and Data Driven Development, Hybrid AI, Team Coordination, Robust Multi-object Detection
Team Report: N/A


SPQR Team
Italy

Team Contact:
Prof. Daniele Nardi, Vincenzo Suriani

Institutes:
Department of Computer, Control and Managemente engineering “Antonio Ruberti” at La Sapienza University of Rome

Team Profile: SPQR is the group of the Department of Computer, Control, and Management Engineering “Antonio Ruberti” at Sapienza University of Rome (Italy). SPQR Team has been involved in RoboCup competitions since 1998 in different leagues: Middle-size 1998-2002, Four-legged 2000-2007, Real rescue robots 2003-2006, @Home in 2006, Virtual-rescue since 2006 and Standard Platform League (SPL) since 2008. SPQR team members published a total of 18 papers in RoboCup Symposia (including best paper awards in 2006 and 2015), in addition to many other publications about RoboCup-related activities on International Journals and Conferences in Artificial Intelligence and Robotics (including IROS RoboCup Best Paper Award in 2016).
Research Topics: Multi-robot coordination, Multi-object tracking, Robot  learning, Perception, Localization.
Team Report: 2018 Team Description Paper

Starkit
Russia

Team Contact:
Sergey Semendyaev
Institutes:
Moscow Institute of Physics and Technology (MIPT)

Team Profile: The Starkit team was organized in the autumn of 2018 in the Moscow Institute of Physics and Technology (MIPT), Russia, on the base of the Laboratory of Wave Processes and Control Systems. The founder of the team is an honorary graduate of MIPT – Azer Babaev. The team leader is Sergey Semendyaev. The SPL team captains are Roman Gorb and Aleksey Kozinov. 

The team has two subteams – Humanoid League team and Standard Platform League team. Both teams consist of students that have to learn a lot of new specific information to participate in the Robocup competition since it is a new field of research in our institution. Our external goal is to participate and preferably to win RoboCup competitions. Our internal goal (inside MIPT) is to obtain knowledge in humanoid robotics and artificial intelligence and to teach new generations of students in this field.

Research Topics: mechatronics, robot design, artificial intelligence
Team Report: Team Research Report for RoboCup 2021


UT Austin Villa
USA

Team Contact:
Peter Stone, Sid Desai

Institutes:
Department of Computer Science, The University of Texas at Austin

Team Profile: Our team is from the University of Texas at Austin. We participated in the Aibo league starting in 2003 and started with the Naos in 2007. We also field a team in the RoboCup 3D simulation league. We won the 2009, 2010, 2012, 2016 and 2018 SPL US Opens. At the international RoboCup SPL competitions, we made the quarterfinals in 2009, 2015 and 2018, finished in 4th place in 2017, finished in 3rd place in 2010 and 2013, finished in 2nd place in 2016, and won the championship in 2012.
Research Topics: Self localization, vision algorithms, multi-agent task allocation, obstacle avoidance, reinforcement learning, ad hoc teamwork, learned humanoid locomotion, Sim2Real learning
Team Report: 2019 Team Report