Rescue Robots A social relevant application Arnoud Visser DOAS Kick-off 7 January 2008.

Slides:



Advertisements
Similar presentations
CONCEPTUAL WEB-BASED FRAMEWORK IN AN INTERACTIVE VIRTUAL ENVIRONMENT FOR DISTANCE LEARNING Amal Oraifige, Graham Oakes, Anthony Felton, David Heesom, Kevin.
Advertisements

School of Computing FACULTY OF ENGINEERING School of Computing FACULTY OF ENGINEERING Personalised On-the-Job Reflective Mobile Learning in Fire and Rescue.
MULTI-ROBOT SYSTEMS Maria Gini (work with Elizabeth Jensen, Julio Godoy, Ernesto Nunes, abd James Parker,) Department of Computer Science and Engineering.
Robocup ve USARSIM Dr. Muhammet Balcılar. What is RoboCup? an international research and education initiative an attempt to foster AI and intelligent.
ESTIMATION OF EARTHQUAKE DAMAGE FROM AERIAL IMAGES BY PROBABILISTIC METHOD Shota Izaka, Hitoshi Saji (Shizuoka University)
Maria Gini Department of Computer Science and Engineering University of Minnesota.
Artificial Intelligence
Spatial analysis in the next decade Department of Urban Engineering University of Tokyo Yukio Sadahiro.
A Summary of the Article “Intelligence Without Representation” by Rodney A. Brooks (1987) Presented by Dain Finn.
Gaze Awareness for Videoconferencing: A Software Approach Nicolas Werro.
A.Kleiner*, N. Behrens** and H. Kenn** Wearable Computing meets MAS: A real-world interface for the RoboCupRescue simulation platform Motivation Wearable.
USARsim & HRI Research Michael Lewis. Background.. USARsim was developed as a research tool for an NSF project to study Robot, Agent, Person Teams in.
Grand Challenges Robert Moorhead Mississippi State University Mississippi State, MS 39762
Lecture 4: Perception and Cognition in Immersive Virtual Environments Dr. Xiangyu WANG.
João Frazão An Agent-Oriented Software Architecture for Teams of Robots. RESCUE PROJECT João Frazão.
Robotic Systems Trends, Research, Future CSCi 338 :: Distributed Systems :: Fall 2005 Aleksandar Stefanovski.
Robotics: Integrated Systems Design. Where are the Robots? Industrial Robots.
Participating in the Rescue Robot League category Motivated by Hanshin Earthquake (Japan 1995) Yearly Competition; First event held in Japan (2001)
Robots, robots, everywhere CS 4 HS, July 20 – July 22.
Robots at Work Dr Gerard McKee Active Robotics Laboratory School of Systems Engineering The University of Reading, UK
Biointelligence Laboratory School of Computer Science and Engineering Seoul National University Cognitive Robots © 2014, SNU CSE Biointelligence Lab.,
Mobiles Robotics: Integrated Systems Design. Where are the Robots? Exploration.
Developing Effective Questioning In Teaching Games For Understanding (TGfU) Pearson & Webb, 2008.
Kansas State University Department of Computing and Information Sciences CIS 830: Advanced Topics in Artificial Intelligence From Data Mining To Knowledge.
UCDMP Saturday Series Secondary Session 3 January 26, 2013.
 1. Which is not one of the six principles that address crucial issues fundamental to all school math programs? A. Curriculum B. Assessment C. Measurement.
Sérgio Ronaldo Barros dos Santos (ITA-Brazil) Sidney Nascimento Givigi Júnior (RMC-Canada) Cairo Lúcio Nascimento Júnior (ITA-Brazil) Autonomous Construction.
Nuttapon Boonpinon Advisor Dr. Attawith Sudsang Department of Computer Engineering,Chulalongkorn University Pattern Formation for Heterogeneous.
Joint International Master Project Dennis Böck & Dirk C. Aumueller 1.
Multiple Autonomous Ground/Air Robot Coordination Exploration of AI techniques for implementing incremental learning. Development of a robot controller.
Intelligent Mobile Robotics Czech Technical University in Prague Libor Přeučil
The Yellow Group Design Informatics (Regli, Stone, Kusiak, Leifer, Gupta, Chung, Fenves, Law, Kopena)
Standards for Mathematical Practice
Boundary Assertion in Behavior-Based Robotics Stephen Cohorn - Dept. of Math, Physics & Engineering, Tarleton State University Mentor: Dr. Mircea Agapie.
Chapter 13 Artificial Intelligence and Expert Systems.
The RoboCup-Rescue Committee The RoboCup Federation
Mobiles Robotics: Integrated Systems Design. Where are the Robots? Exploration.
Riga Technical University Department of System Theory and Design Usage of Multi-Agent Paradigm in Multi-Robot Systems Integration Assistant professor Egons.
Chapter 4 Decision Support System & Artificial Intelligence.
Human Computer Interaction
Algorithmic, Game-theoretic and Logical Foundations
___________________________________________________ Intelligent Planning and Collaborative Systems for Emergency Response
Robotics Club: 5:30 this evening
KNOWLEDGE BASED SYSTEMS
INTELLIGENT AGENTS. Agents  An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through.
Mutual Empowerment in Human-Agent-Robot Teams 16 December 2010 HART Workshop Jurriaan van Diggelen.
Internet of Things. IoT Novel paradigm – Rapidly gaining ground in the wireless scenario Basic idea – Pervasive presence around us a variety of things.
‘Activity in Context’ – Planning to Keep Learners ‘in the Zone’ for Scenario-based Mixed-Initiative Training Austin Tate, MSc in e-Learning Dissertation.
Scaling Human Robot Teams Prasanna Velagapudi Paul Scerri Katia Sycara Mike Lewis Robotics Institute Carnegie Mellon University Pittsburgh, PA.
Ghislain Fouodji Tasse Supervisor: Dr. Karen Bradshaw Computer Science Department Rhodes University 24 March 2009.
A field of study that encompasses computational techniques for performing tasks that require intelligence when performed by humans. Simulation of human.
Approved for public release; distribution is unlimited. 10/7/09 Autonomous Systems Sensors – The Front End of ISR Mr. Patrick M. Sullivan SPAWAR ISR/IO.
World Geography Chapter 1. The Study of Geography Section 1.
ParkNet: Drive-by Sensing of Road-Side Parking Statistics Irfan Ullah Department of Information and Communication Engineering Myongji university, Yongin,
Network Management Lecture 13. MACHINE LEARNING TECHNIQUES 2 Dr. Atiq Ahmed Université de Balouchistan.
University of Pennsylvania 1 GRASP Control of Multiple Autonomous Robot Systems Vijay Kumar Camillo Taylor Aveek Das Guilherme Pereira John Spletzer GRASP.
Louise Hunter. Background Search & Rescue Collapsed caves/mines Natural disasters Robots Underwater surveying Planetary exploration Bomb disposal.
Mathematical Practice Standards
Design and Organization of Autonomous Systems 7 January 2008
WP2 INERTIA Distributed Multi-Agent Based Framework
Schedule for next 2 weeks
Timothy Boger and Mike Korostelev
Multi-Agent Exploration
Engineering Agent Systems for Decision Support
DrillSim July 2005.
Introduction to Artificial Intelligence Instructor: Dr. Eduardo Urbina
Modeling and Analysis Tutorial
Chapter 12 Analyzing Semistructured Decision Support Systems
Kostas Kolomvatsos, Christos Anagnostopoulos
9/28/18 – Earthquake and Tsunami hit Indonesia
Presentation transcript:

Rescue Robots A social relevant application Arnoud Visser DOAS Kick-off 7 January 2008

Urban Search & Rescue (USAR) Research in USAR robotics is a vigorous research area Offers unique challenges that are difficult to create in a lab environment Image from RoboCamp 2006 Tutorial

Applications of rescue robots After the Oklahoma City bombing (1995), J. Blitch took notes as to how robots might have been applied. The trigger for the RoboCup Rescue initiative was the Hanshi-Awaji earthquake which hit Kobe City on the same year. Rescue robots were first used at the WTC 9/11 (2001). M. Micire analyzed the operations and identified seven research topics for the robotics community. After 2001, rescue robots were applied in several occasions: –Aerial robots were used after hurricane Katrina and Rita –Boat robots after hurricane Wilma

Rescue Robots Mini robots Bomb-squad robots Construction robots

Analysis the USAR operations

Recommendations [1] 1.Research in image processing is needed for fast and accurate victim detection. 2.Automated tether management is needed for robot mobility assistance. 3.Methodologies to increase the quality of wireless communication is required for robots traveling deep into void structures. 4.Research must continue for small robots that can adaptively optimize their shape in difficult void structures. 5.Localization and mapping must be expanded to include highly unstructured domains. 6.Operator assistance through size and depth estimation techniques should be researched. 7.Assisted navigation techniques in highly irregular confined spaces must be explored to limit the number of pose and robot state errors. [1] M. Micire, "Analysis of the Robotic-Assisted Search and Rescue Response to the World Trade Center Disaster," Masters Thesis, University of South Florida, July 2002.

RoboCup Rescue Competitions Infrastructure simulation –Distributed decision making –Cooperation –Simulations of: Building collapses Road Blockages Spreading fire Traffic Real Robots –Single collapsed structure –Autonomous navigation –Victim location and assessment

Virtual Robot Competition Autonomous multi-robot control Human, multi-robot interfaces 3D mapping and exploration of environments by multi- robot teams Development of novel mobility modes and sensor processing skills Lower entry barriers for developers Competition based upon USARSim software

What is USARSim? High-fidelity multi-robot simulator developed on top of an existing game engine –High performance physics and 3D rendering Originally conceived as tool for Urban Search and Rescue (USAR), it has a much broader breadth

Basic Premise Would like to be able to develop, debug, and evaluate cognitive systems –Repeatable trials –Known ground truth, noise, detections, false detections Evaluation environment should provide realism –Realistic complexity –Tailored data output –Environmental interaction –Obey basic laws of physics in sensing and mobility Images from USARSim / MOAST Tutorial

Illustrative Example What would an intelligent system need from this environment? –Extracted information? –Environmental interaction? –External knowledge?

One Possible Answer Ontology & Symbolic Data Server Information Wireframe Polygon Surface Models Symbolic: Chair, Properties: table, ? Geometric/Symbolic

World Interaction Physics based interactions with world provide: –Realistic dangers to robot –Cues about object relationships –Mobility and manipulation challenges –…

World Interactions Ontology & Symbolic Data Server Symbolic Information Movement shows correct segmentation, which leads to… Symbolic: Properties: Chair

Previous Scenario Depicts an Embodied Intelligent Agent Environment – provides some place to exist and objects to interact with Embodiment – provides some way to move around in and effect change of the environment Intelligence – provides some way to reason over percepts and to decide on appropriate actions Image from Russell, Norvig Artificial Intelligence

Conclusion Research in Rescue Robots is socially relevant. Currently working on two of Micire’s topics: Localization in unstructured environments Accurate Mapping with multiple robots Information needed to optimize exploration