Qua­li­fi­ca­ti­on Ma­te­ri­al

Ad­ap­ti­ve Mo­del-Ba­sed Mo­ni­to­ring for Ro­bots (Int. Con­fe­rence Pa­per, 2014)

Kirchner, Dominik ; Geihs, Kurt: Adaptive Model-based Monitoring for Robots. In: 13th International Conference on Intelligent Autonomous Systems (IAS). Padova, Italy, 2014


Continuous and comprehensive monitoring is a key requirement for reliable failure detection. However, the overhead of the observation process conflicts with the limited resources of a robot platform. Therefore, robot monitoring faces high efficiency requirements. This defines a trade-off between comprehensive observation and monitoring resource overhead. In this paper, we propose an adaptive, model-based monitoring approach that addresses this trade-off. We specify an individual monitoring configuration in an abstract system model to focus the observation on expressive state aspects. Moreover, we introduce adaptivity to further improve the efficiency of the monitoring process. To evaluate this efficiency, we compare our approach with a reference monitoring system. Due to our results, we are confident that the proposed approach significantly reduces the resource overhead.

Ro­SHA: A Mul­ti-Ro­bot Self-Hea­ling Ar­chi­tec­tu­re (Int. Con­fe­rence Pa­per, 2013)

Kirchner, D, Niemczyk S, Geihs K. 2013. RoSHA: A Multi-Robot Self-Healing Architecture. 17th Annual RoboCup International Symposium.


Reliability is one of the key challenges in multi-robot systems to increase practicable applicability and hence the commercial usage. This paper presents RoSHA, a self-healing architecture for multi-robot systems. RoSHA is based on the established robot middleware ROS and provides components for application independent analysis and repair. A plug-in architecture enables the developer to simply add new components for repair and analysis. Bayesian networks are used to diagnose failures and their root causes. ALICA, a domain specific language for multi-robot systems, is applied to coordinate recovery plans in multi-robot systems.

Mo­del­ling and Con­trol­ling of Be­ha­viour for Au­to­no­mous Mo­bi­le Ro­bots (Book, 2013)

Skubch, H. 2013. Modelling and Controlling of Behaviour for Autonomous Mobile Robots.


As research progresses, it enables multi-robot systems to be used in more and more complex and dynamic scenarios. Hence, the question arises how different modelling and reasoning paradigms can be utilised to describe the intended behaviour of a team and execute it in a robust and adaptive manner. Hendrik Skubch presents a solution, ALICA (A Language for Interactive Cooperative Agents) which combines modelling techniques drawn from different paradigms in an integrative fashion. Hierarchies of finite state machines are used to structure the behaviour of the team such that temporal and causal relationships can be expressed. Utility functions weigh different options against each other and assign agents to different tasks. Finally, non-linear constraint satisfaction and optimisation problems are integrated, allowing for complex cooperative behaviour to be specified in a concise, theoretically well-founded manner.

Co­ope­ra­ti­ve Path Plan­ning for Mul­ti-Ro­bot Sys­tems in Dy­na­mic Do­mains (Book Chap­ter, 2011)

Opfer, S, Skubch H, Geihs K. 2011. Cooperative Path Planning for Multi-Robot Systems in Dynamic Domains. Mobile Robots - Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator Training. 237-258.


This publication is one chapter of several chapters combined to a book about mobile robots in general. Therefore, there is no abstract as part of this publication. Nevertheless, the chapter is freely available.

A Mo­del­ling Lan­gua­ge for Co­ope­ra­ti­ve Plans in High­ly Dy­na­mic Do­mains (Jour­nal Pa­per, 2011)

Skubch, H, Wagner M, Reichle R, Geihs K. 2011. A modelling language for cooperative plans in highly dynamic domains. Mechatronics. 21:423-433


Cooperative behaviour is one of the challenges most pronounced in the RoboCup Middle Size League. Especially the dynamic nature of the domain, which calls for swift adaptation by each robot and the team as a whole, is a distinctive property of the league. The ability to establish highly responsive teamwork while facing unreliable communication and sensory noise is a key to successful soccer teams. Moreover, modelling such responsive, cooperative behaviour is difficult. In this work, we specify a novel model for cooperative behaviour geared towards highly dynamic domains, focussing on the language syntax and semantics. In our approach, agents estimate each other’s decision and correct these estimations once they receive contradictory information. We provide a comprehensive approach for agent teamwork featuring intuitive modelling capabilities for multi-agent activities, abstractions over activities and agents, and a clear operational semantics. Moreover, we briefly present a graphical modeling tool for cooperative strategies, which is based directly on the theory laid out, together with a practical framework for executing said strategies. We show experimentally the responsiveness and coherence of the resulting team play.

Per­for­mance in Past Events (last 3 ye­ars)

  • 3rd place at the RoboCup Portuguese Open 2014
  • 5th place at the RoboCup World Champion Ship 2013
  • 2nd place at the Technical Challenge of the RoboCup World Champion Ship 2013

Team De­scrip­ti­on Pa­per/In­no­va­tions

  • The Carpe Noctem Cassel Team Description Paper 2016

Cont­ri­bu­ti­on to the Ro­bo­Cup MSL com­mu­ni­ty


  • Andreas Witsch (Team Leader) is member of the RoboCup MSL Executive Committee
  • Andreas Witsch (Team Leader) is member of the German National RoboCup MSL Commitee
  • Stephan Opfer (Team Leader) is member of the Extended-Local-Organizing Committee for the RoboCup World Championship 2016 in Leipzig
  • Dominik Kirchner (Former Team Leader) is member of the Extended-Local-Organizing Committee for the RoboCup World Championship 2016 in Leipzig
  • Philipp Baer (Former Team Leader) was league chair at the German Open 2008 and 2009


The team hosted several International RoboCup MSL Workshops.

  • 1st Workshop in 2008
  • 3rd Workshop in 2013
  • 6th Workshop in 2016 (acknowledged at the 5th Workshop)


The team believes in the principles of open-source software. Therefore, our complete software is publicly available at GitHub.com. This even includes our current high-level strategies and controllers - simply everything! The repositories that are relevant for the MSL are:

  • Alica - Our High-Level Strategie and Behaviour Modelling Engine
  • Alica Plan Designer - The Graphical Modelling Software for Hierarchical Multi-Agent Plans
  • CNC-MSL - Our repository for sensor fusion algorithms, world modelling, path planning, developed strategies, plans and everything else...
  • CNC-MSLDriver - Our repository for hardware drivers, relevant only for our robots itself (Camera Driver, Motion Driver, Calibration Tools, CAN-Bus, Kinect Driver)
  • Supplementary - This repository collects all general useful software libraries (Configuration-File Reading, Communication Proxies, Process Manager, Visual Debugging Tools, General CSP-Solving Techniques).

Me­cha­ni­cal and Electri­cal De­scrip­ti­on and Soft­ware Flow­chart


  • New Omni-Vision Concept: Drawings, CAD-Files (The files are created with Creo from PTC. It is freely available for students.)
  • New Kicker and Ball Handling Concept: Drawings, CAD-Files (The files are created with Inventor from Autodesk. Also freely available for students.)
  • The CAD-Files of the new Kicker and Ball Handling Concept also include the most recent CAD-Files of our complete robots.


The EAGLE Schema and Layout files for all our custom circuit boards. A limited but free license for EAGLE is available. There are also packages for Ubuntu.

  • Actuator Board: controls the active dribbling device and reads all secondary sensors (buttons, IMU, light barrier)
  • Kicker Board: charges the kick capacitor and releases a kick on command
  • Power-Supply Board: measures battery voltage, controls power-supply for each hardware module separately, and allows for seamless switching between internal (battery) and external power-supply (via cable)

Software Flowchart:

  • The software flow chart of the Carpe Noctem Software Architecture