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Virtual Robots RoboCupRescue Competition: Contributions to Infrastructure and Science. USAR Challenge. Rapid Advancement in USAR 2001-present. Simulation League : communication models to cooperation & learning

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Virtual Robots RoboCupRescue Competition: Contributions to Infrastructure and Science

rapid advancement in usar 2001 present
Rapid Advancement in USAR2001-present

Simulation League: communication models to cooperation & learning

[Kitano and Tadokoro, 2001] H. Kitano and S. Tadokoro, Robocup rescue: A grand challenge for multiagent and intelligent systems. AI Magazine, 22(1):39–52, 2001.

Robot Rescue League:video driven teleoperation to 3D scanning & autonomous exploration

[Jacoff et al., 2001] A. Jacoff, E. Messina, J. Evans, Experiences in deploying test arenas for autonomous mobile robots, Proceedings of the 2001 Performance Metrics for Intelligent Systems (PerMIS) Workshop, Mexico City, Mexico, 2001.

our first team
Our first team





Mobility comes to dominate Rescue Robot competition by 2005



RED ARENA with Random Step Fields and other difficult mobility

Obstacles is for very agile robots, all control modes are allowed.

virtual robots as a bridge
Virtual Robots as a Bridge

VR  Physical League

  • Continually improving simulation quality and validation

VR Simulation League

  • Expanding team size & problem complexity
usarsim architecture simulation desiderata
USARsim Architecture Simulation Desiderata
  • Expense and availability of simulation hardware and software to USAR robotics community
  • Ease of programming to reflect targeted aspects of design
  • Fidelity of simulation w.r.t. aspects of design to be tested
usarsim architecture simulation requirements
USARsim Architecture SimulationRequirements

Video feedfor teleoperation and visual search and identification

Sensor simulation- for autonomous control and fused displays

Simulated robot dynamics- for teleoperation and autonomous control

Multiple entity simulation- to allow interaction and cooperation among teams of robots

usarsim architecture

Image server

USARsim Architecture

The image server captures images from video memory so they can be subjected to visual processing just like input from a real camera.

COTS game engine supplies best available graphics & physics engines Standard tools like 3D studio max or Maya are available

Robots are controlled and sensor data gathered from sockets into the game

brief history 2003
Brief history 2003
  • Developed USARsim simulation
  • Limited to our own robots
  • Limited to our own (RETSINA) control architecture
  • Demo’d
  • USAR workshop at USF
  • US Open RoboCup



brief history 2004
Brief history 2004
  • Extended simulator for general access & added features such as sensor models & image server needed for research
  • Modeled robots commonly used robots
  • Made control architecture agnostic
  • Added plug-in/API for popular
  • middleware
    • Player/(Stage)
    • Pyro
  • Presented to USAR participants at
  • Robocup 2004 in Lisbon




brief history 2005
Brief history 2005

Demo approved at Robocup Rescue Camp in Rome

Rule: robots must model real robots being used by team in USAR

6 teams from 4 countries participated in demo competition at Robocup in Osaka

University of Rome, International University of Bremen, University of Osnabruck, University of Freiburg, Meijo University, University of Pittsburgh

Virtual Robots USAR competition approved to become new competition within RobocupRescue League start for RoboCup 2006 in Bremen June 14-20

USARSim moved to Source Forge





brief history 2006
Brief history 2006

USARSim Units regularlized by NIST

Mission Package designed to accommodate extensions to simulation

First RoboCup Rescue VR competition held in Bremen8 teams from 6 countries

1st Freiburg, 2nd I U Bremen, 3rd Amsterdam







brief history 2007
Brief history 2007

Operator penalty repealed (as in RR league)

Communications server added

Second RoboCup Rescue VR competition held in Atlanta8 teams from 5 countries

1st Pitt/CMU, 2nd Jacobs, 3rd Rome

Continuing work in validation and new platforms








brief history 2008
Brief history 2008

Third RoboCup Rescue VR competition held in Sizhou, China 10 teams from 8 countries

UAVs added

1st SEU, 2nd UC Merced, 3rd CMU/Pitt

German Open 3 teams, Iranian Open 4 teams








brief history 2009
Brief history 2009

Fourth RoboCup Rescue VR competition held in Graz, Austria11 teams from 8 countries

1st UC Merced, 2nd SEU, 3rd Amsterdam-Oxford

German Open 3 teams, Iranian Open 4 teams

Continuing work in validation and new platforms








usarsim robots


Legged Robot

Ground Vehicle

Aerial Vehicle

Nautic Vehicle

Skid Steered


Ackerman Steered


Rotary Wing






















USARSim – Robots


11 usarsim validation studies
11 USARSim Validation Studies
  • Synthetic video
    • Carpin, S., Stoyanov, T., Nevatia, Y., Lewis, M. and Wang, J. (2006a). Quantitative assessments of USARSim accuracy". Proceedings of PerMIS 2006
  • Hokuyo laser range finder
    • Carpin, S., Wang, J., Lewis, M., Birk, A., and Jacoff, A. (2005). High fidelity tools for rescue robotics: Results and perspectives, Robocup 2005 Symposium.
  • Platform physics & behavior
    • Sven Albrecht, Joachim Hertzberg, Kai Lingemann, Andreas N¨uchter, Jochen Sprickerhof, Stefan Stiene (2006). Device Level Simulation of Kurt3D Rescue Robots, Third International Workshop on Synthetic Simulation and Robotics to Mitigate Earthquake Disaster, 2006.
    • Carpin, S., Lewis, M., Wang, J., Balakirsky, S. and Scrapper, C. (2006b). Bridging the gap between simulation and reality in urban search and rescue. Robocup 2006: Robot Soccer World Cup X, Springer, Lecture Notes in Artificial Intelligence
    • Nicola Greggio, Gianluca Silvestri, Emanuele Menegatti, Enrico Pagello (2007). A realistic simulation of a humanoid robot in USARSim, Proceeding of the 4th International Symposium on Mechatronics and its Applications (ISMA07) , 2007
    • S. Okamoto, A. Jacoff, S. Balakirsky, and S. Tadokoro (2007). Qualitative validation of a serpentine robot in USARSim Proceedings of the 2007 JSME Conference on Robotics and Mechatronics, 2007.
    • Okamoto, S.   Kurose, K.   Saga, S.   Ohno, K.   Tadokoro, S.   Validation of Simulated Robots with Realistically Modeled Dimensions and Mass in USARSim, IEEE International Workshop on Safety, Security and Rescue Robotics, 2008. (SSRR 2008), 77-82, 2008.
    • Lewis, M., Hughes, S., Wang, J., Koes, M. and Carpin, S., Validating USARsim for use in HRI research, Proceedings of the 49th Annual Meeting of the Human Factors and Ergonomics Society, Orlando, FL, 457-461, 2005.
    • Pepper, C., Balakirsky, S. and Scrapper, C., Robot Simulation Physics Validation, Proceedings of PerMIS’07, 2007.
    • Taylor, B., Balakirsky, S., Messina, E. and Quinn, R., Design and Validation of a Whegs Robot in USARSim, Proceedings of PerMIS’07.
    • Zaratti, M., Fratarcangeli, M., and Iocchi, L., A 3D Simulator of Multiple Legged Robots based on USARSim. Robocup 2006: Robot Soccer World Cup X, Springer, LNAI, 2006.

contributions to scientific infrastructure
Contributions to Scientific Infrastructure
  • Competition provided critical mass of users to benefit from network externalities
  • Association with competition provided justification for NIST development & support
  • Involving more parties led to greater standardization & more general utility
reported studies using usarsim
Reported Studies Using USARSim
  • 14 Human-Robot Interaction studies-9 groups
  • Dialog management – 2 groups
  • Machine learning- 2
  • Testing control algorithms
  • Driving behavior- 2 groups
  • Social interaction
  • Service composition for robots
  • Self diagnosis
project infrastructure
Project Infrastructure
  • Developed under NSF ITR
  • Used in MURIs
    • CMU
    • Berkeley
    • MIT
  • ONR Science of Autonomy
multi robot mapping evaluating map quality
Multi-Robot Mapping & Evaluating Map Quality
  • Direct contribution of competition
  • Upcoming Special issue of Autonomous Robots
  • special sessions on mapping and map quality at PerMIS’08 and RSS’08 workshops
  • Other venues

Luca Iocchi and Stefano Pellegrini (2007). Building 3D maps with semantic elements integrating 2D laser, stereo vision and IMU on a mobile robot, Proceedings of the 2nd ISPRS International Workshop on 3D-ARCH, 2007.

Max Pfingsthorn, Bayu Slamet and Arnoud Visser,(2007). A Scalable Hybrid Multi-robot SLAM Method for Highly Detailed Maps, Lecture Notes in Computer Science, RoboCup 2007: Robot Soccer World Cup XI, 385-392, 2008.

V. Sakenas, O.  Kosuchinas, M. Pfingsthorn,  A. Birk,(2007).  Extraction of Semantic Floor Plans from 3D Point Cloud Maps, IEEE International Workshop on Safety, Security and Rescue Robotics, 2007. SSRR 2007, 1-6, 2007.

D. Sun, A. Kleiner, and T. M. Wendt (2008). "Multi-Robot Range-Only SLAM by Active Sensor Nodes for Urban Search and Rescue", in In Robocup 2008: Robot Soccer World Cup XII, 2008.

I. Varsadan, A. Birk, and M. Pfingsthorn (2008). "Determining Map Quality through an Image Similarity Metric", Proceedings CD of the 12th RoboCup International Symposium, Suzhou, China.

elemental tests
Elemental Tests

Because contests reward composite performance they tend to promote teams with the strongest “weakest link” rather than promoting the strongest solutions.


  • Sharing winning code (Agent simulation & VR)
  • Elemental tests as part of competition
competition updates 2009
Competition updates 2009
  • Preliminary rounds based on automatically scored elemental tests
  • Rationale:
    • Identify “best in class” abilities
    • Push teams to attack new challenges
    • Move towards objectively measurable performance metrics
first elemental test
First elemental test
  • Mapping
  • Reward the ability to produce a map that allows a first responder to reach a set of random points in the disaster scenario
    • Ignore metric quality, but focus on topological utility
    • Automatically scored
second elemental test
Second elemental test
  • Radio network deployment challenge
  • Reward teams able to identify deployment points yielding the maximum coverage for a given environment
    • A priori data partially wrong
    • Reward planning and the ability to navigate to target points
    • Automatically scored (score is the covered area)
    • Fully autonomous challenge
    • Uses a newly developed Wireless simulator taking into account walls, attenuation, etc..
third elemental test
Third elemental test
  • Teleoperation
  • Reward teams able to develop an HRI where a single operator can drive a team of robots to a set of goal locations
    • Automatically scored
    • Very different target locations impose the use of heterogeneous robot teams (flying, wheeled, tracked)
    • Semiautonomous test
next challenge
Next Challenge
  • Can contest & simulator survive change in platform?
  • UE2 engine cannot support large numbers of robots (~8) with high fidelity
  • UE2 engine cannot support physics intensive dynamics such as tracks
  • Moving to UE3 requires re-doing most of the infrastructure
performance for tracked robots
Performance for tracked robots

Modeling something with many constraints such as tracks is extremely difficult. In the case of this Tarantula, for example, simplifying tracks to 5 wheels/flipper yields: 20 x 5 + 4x6 = 124 constrained dof and is just about at the limit of the Karma engine. This simplification of a tracked robot is about 5 times as costly to simulate as a 4 wheeled platform.