Virtual Robots
RoboCupRescue Competition:
Contributions to Infrastructure
and Science
Michael Lewis
School of Information
Sciences
University of Pittsburgh
Pittsburgh, PA
Stefano Carpin
School of
Engineering
University of
California, Merced
Merced, CA
Stephen Balakirsky
Intelligent Systems
National Institute of
Standards and
Technology
Gaithersburg, MD
USAR Challenge
Rapid Advancement in USAR
2001-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
Tarantula
Pioneer
PERs
2004 USAR winners in Lisbon
Mobility comes to dominate Rescue Robot
competition by 2005
INSERT VIDEO HERE
RAPTOR, CARNEGIE MELLON and UNIV. OF PITTSBURGH, USA
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
VR  Physical League
• Continually improving simulation quality
and validation
VR Simulation League
• Expanding team size & problem
complexity
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
Video feed for 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
Team Cooperation
COTS game engine
supplies best
available graphics &
physics engines
Standard tools like
3D studio max or
Maya are available
Controller
Controller
High Level
Control
High Level
Control
Middle Level
Control
……
Middle Level
Control
Control
Interface
Control
Interface
Video Feedback
Video Feedback
Unreal Client
(Attached spectator)
Unreal Client
(Attached spectator)
The image
server captures
images
from
Robots
are controlled
video data
memory
and sensor
gathered
fromcan
sockets
so they
be
into the
game to
subjected
visual
processing just
like input from a
real camera.
Network
Gamebots
Unreal Data
Control Data
Unreal Engine
Map
Models (Robots model, Sensor
model, victim model etc.)
Image server
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
2002
2003
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
2002
2003
2004
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
2002
2003
2004
2005
USARSim Aibo model presented by Marco
Zaratti at 2005 RoboCup Symposium
Brief history 2006
USARSim Units regularlized by NIST
Mission Package designed to accommodate
extensions to simulation
First RoboCup Rescue VR competition held
in Bremen 8 teams from 6 countries
1st Freiburg, 2nd I U Bremen, 3rd Amsterdam
2002
2003
2004
2005
2006
2007
2006 Competition World
Brief history 2007
Operator penalty repealed (as in RR league)
Communications server added
Second RoboCup Rescue VR competition
held in Atlanta 8 teams from 5 countries
1st Pitt/CMU, 2nd Jacobs, 3rd Rome
Continuing work in validation and new
platforms
2002
2003
2004
2005
2006
2007
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
2002
2003
2004
2005
2006
2007
2008
Brief history 2009
Fourth RoboCup Rescue VR competition held in
Graz, Austria 11 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
2002
2003
2004
2005
2006
2007
2008
USARSim – Sensors
USARSim – Robots
KRobot
Joint efforts
Legged Robot
Ground Vehicle
Skid Steered
Robot
AIBO
P2AT
Kurt2D
QRIO
P2DX
Kurt3D
Zerg
ATRVJr
Lisa
Aerial Vehicle
Nautic Vehicle
Ackerman Steered Rotary Wing
Robot
Robot
AirRobot
Cooper
Hummer
Talon
Soryu
Underwater
Robot
Submarine
Sedan
TeleMax
SnowStorm
11 USARSim Validation Studies
•
Synthetic video
–
•
Hokuyo laser range finder
–
•
Carpin, S., Stoyanov, T., Nevatia, Y., Lewis, M. and Wang, J. (2006a). Quantitative assessments of
USARSim accuracy". Proceedings of PerMIS 2006
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, 457461, 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.
Validation: simulation & real P3-AT
run from same input
USARSim Downloads
60000
50000
40000
30000
20000
10000
0
2005
2006
2007
2008
2009
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
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•
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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
Theses & Projects
4
3
2
1
0
competitors
noncompetitors
Project Infrastructure
• Developed under NSF ITR
• Used in MURIs
– CMU
– Berkeley
– MIT
• ONR Science of Autonomy
• DARPA SyNAPSE
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
Because contests reward composite
performance they tend to promote teams
with the strongest “weakest link” rather
than promoting the strongest solutions.
Solutions:
• Sharing winning code (Agent simulation &
VR)
• Elemental tests as part of competition
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
• 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
• 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
• 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
• 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
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.