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Virtual Robots RoboCupRescue Competition: Contributions to Infrastructure
and ScienceMichael 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 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
Tarantula
PERs
Pioneer
2004 USAR winners in Lisbon
RAPTOR, CARNEGIE MELLON and UNIV. OF PITTSBURGH, USA
INSERT VIDEO HERE
RED ARENA with Random Step Fields and other difficult mobilityObstacles is for very agile robots, all control modes are allowed.
Mobility comes to dominate Rescue Robot competition by 2005
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
Unreal Engine
Map Models (Robots model, Sensor model, victim model etc.)
Gamebots
Network
Control Interface
Unreal Client (Attached spectator)
Middle Level Control
High Level Control
Controller
Video Feedback
Controller
Unreal Client (Attached spectator)
Video Feedback
……
Team Cooperation
Unreal Data
Control Data
Control Interface
Middle Level Control
High Level Control
Image server
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
The image server captures images from video memory so they can be subjected to visual processing just like input from a real camera.
Brief history 2003
2002 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
2002 2003 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
2002 2003 2004 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
USARSim Aibo model presented by Marco Zaratti at 2005 RoboCup Symposium
Brief history 2006
2002 2004 2005 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
2003 2007
2006 Competition World
Brief history 2007
2002 2004 2005 2006
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
2003 2007 2008
Brief history 2008
2002 2004 2005 2006
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
2003 2007 2008
Brief history 2009
2002 2004 2005 2006
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
2003 2007 2008
USARSim – Sensors
USARSim – Robots
Skid SteeredRobot
Aerial VehicleGround VehicleLegged Robot
Ackerman SteeredRobot
UnderwaterRobot
AirRobot
ATRVJr
Cooper
AIBO
Hummer
Kurt2D
Kurt3D
Lisa
Nautic Vehicle
P2AT
P2DXQRIO
Rotary WingRobot
Sedan SnowStorm
TeleMax
Submarine
Talon SoryuZerg
KRobotJoint efforts
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.
www.sourceforge.net/project/usarsim
Validation: simulation & real P3-AT run from same input
USARSim Downloads
0
10000
20000
30000
40000
50000
60000
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
• 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
0
1
2
3
4
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 venuesLuca 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.