RescueRobots Freiburg 2006

AI Department | Institute for Computer Science | Faculty for Applied Sciences | University of Freiburg



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RescueRobots Freiburg - RoboCupRescue Robot League Team

RoboCupRescue Robot League

What is RoboCup Rescue?

The RoboCupRescue Real Robot League competition is an international evaluation conference for the RoboCupRescue Robotics and Infrastructure Project research.

The RoboCupRescue Robotics and Infrastructure Project studies future standards for robotic infrastructure built to support human welfare. Currently the NIST USAR arena has been used in several RoboCupRescue and AAAI competitions.

A team of multiple (autonomous or tele-operated) robots moves inside this test arena, divided into thee regions of increasing difficulty levels, searching for victims and building a map of the surrounding environment to be transmitted and/or brought back by the robot(s) to the human operators.

In the research group on Foundations of AI, we use real rescue as a testbed for developing and testing new techniques in Artificial Intelligence and Robotics. In particular, we work on self-localization and navigation, on cooperative sensing and multi-agent cooperation, on rationale action selection and on learning.

About RescueRobots Freiburg

RescueRobots Freiburg is a team of students from the University of Freiburg. The team originates from the former CS Freiburg team, which won the RoboCup world championship in the RoboCupSoccer F2000 league three times, and the ResQ Freiburg team, which won the RoboCup world championship in the RoboCupRescue Simulation league in 2004.

Our research focuses on the implementation of a cheap and fully autonomous team of robots that quickly explores a large terrain while mapping its environment. Our main focus concerns RFID-based SLAM and exploration, autonomous detection of relevant 3D structures, visual odometry, and autonomous victim identification. Furthermore, we introduce a custom made 3D Laser Range Finder (LRF) and a novel mechanism for the active distribution of RFID tags.

RFID-based SLAM and exploration has advantages for Urban Search and Rescue (USAR): We belief that the distribution of RFID tags in the environment can also be very valuable to human task forces equipped with a RFID reader. From recognized RFID tags the system is able to generate a topological map which can be passed to a human operator. The map can be augmented with structural and victim-specific information. Travel paths to victims can directly be passed to human task forces as complete plans that consist of RFID tag locations and walking directions. In fact, tags can be considered as signposts since the topological map provides for each tag the appropriate direction. Given a plan of tags, task forces can find victim locations directly by following the tags, rather than locating themselves on a 2D or 3D metric map beforehand. The idea of labeling locations with information that is important to the rescue task has already be applied in practice. During the disaster relief in New Orleans in 2005, rescue task forces marked buildings with information concerning, for example, hazardous materials or victims inside the buildings. Our autonomous RFID-based marking of locations is a straight forward extension of this concept.

RoboCupRescue confronts the robots with a real 3D problem. In order to find victims, robots have to overcome difficult terrain including ramps, stairs and stepfields. The managing of these tasks autonomously without human control is one goal of our research. Therefore, we started to investigate approaches for visual odometry and 3D structure recognition, which we will present in this paper.

Contact: Alexander Kleiner (homepage)


19. June 2006
  • Our team won the 1st prize
    of the Rescue Autonomy Challenge during
    the RoboCup World Championship in Bremen
    (see autonomy06.avi).

  • 06. June 2006
  • We are preparing our team.

  • Alexander Kleiner, 7. June 2006