Project: Match visualization and analysis


  • Ludovic Hofer (Rhoban FC)
  • Maike Paetzel (Bit-Bots)
  • … (other contributors are welcome)

This projects aim at developing three different tools allowing to create large datasets of games usable by the whole league:

  1. A visualizer to display augmented video streams during and after a match
  2. A labeling tool to annotate games either semi-automatically or automatically
    • Humans can provide/confirm position of objects during the game (ball, robots, referees)
    • Using tracking algorithms to reduce the tagging burden
    • Multiple points of view allow to retrieve 3d position for different objects
  3. An analyzer to extract high-level metrics from the labeled data.
    • Based on information from the GameController and the labeling tool
    • Extract high level metrics such as:
      • robot peak speed
      • Localization accuracy
      • Number of pick-ups


  • Provide more data based on games played during the tournament
  • Make games more understandable and engaging (display robot intentions)
    • For the public
    • For other teams watching the games
  • Allow measurement of the in-game performance of robots
    • Make tracking of performance along the years easier
    • Ensure the event-triggered roadmap is based on reliable information


A first proof of concept has been created and used based on RoboCup 2019 data:

While it already has functional elements it requires drastical modifications:

  • It does only support a custom protocol from Rhoban yet
  • Performance should strongly be improved to allow
  • Ergonomy is basic
  • Some of the dependencies are outdated
  • Documentation and hands-on tutorial should be made available