An Open-Source Virtual Manufacturing Automation Competition
An Open-Source Virtual Manufacturing Automation Competition
An Open-Source Virtual Manufacturing Automation Competition
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Capital Science 2008<strong>An</strong> <strong>Open</strong>-<strong>Source</strong> <strong>Virtual</strong><strong>Manufacturing</strong> <strong>Automation</strong><strong>Competition</strong>Raj Madhavan, Stephen Balakirsky,Chris ScrapperIntelligent Systems DivisionNational Institute of Standards and Technology(NIST)Presented by: Raj Madhavan, Ph.D.raj.madhavan@nist.govMarch 29 th 2008
Capital Science 2008Automated Guided Vehicles (AGVs)• Integral component oftoday’s manufacturingprocess– Intra-factory transport– Truck-trailer (un)loading– …• Typically used in largemanufacturing operations– Large passageways– Little clutter– Large amount ofinfrastructureCertain commercial hardware, software and tools are identified in this paper in order to explain our research. Such identification does not imply recommendation orendorsement by the National Institute of Standards and Technology, nor does it imply that the hardware, software, or tools identified are necessarily the best available forthe purpose.
Capital Science 2008Small & Medium Manufacturers• Present unique challenges for operation inunstructured environment, amongst humans, andwith dynamics• Significant cost entry barrier drives elimination ofexpensive infrastructure
Capital Science 2008Making Manufactures More Competitive• Striving to allow increased automation for small- and mediummanufacturers• NIST does not manufacture/develop commercial robots or controlsystems• NIST does design performance metrics to allow current and potential endusersto competitively compare technology and promote innovation• NIST brings together AGV end users, manufacturers, and researchers tounderstand potential “opportunities for improvement”
Capital Science 2008Three Communities; One PurposeIndustry Developers Researchers• Meet w/ industry to understand high-level needs• Distill needs into individual performance metrics andcompetencies• Involve researchers to crack hard problems• Demonstrate performance to developers through the use ofrepeatable artifacts
Capital Science 2008How To Get Researcher Involvement:<strong>Competition</strong>s!• NIST has a history in designing and operatingUrban Search and Rescue <strong>Competition</strong>s• Promote real-world, relevant research• Prove performance metrics and standards• Provide researchers an opportunity toshowcase their work and compete againstpeersNIST wanted to organize a similarcompetition for manufacturing
Capital Science 2008Motivation and Benefits• Industry benefits– Bring increased exposure to their research problems– Provide a free workforce to solve these problems– Create a pool of students that are available for absorption into theircompanies• Student benefits– Lower the entry barrier for robotics research through the use ofsimulation systems and open source software– Facilitate interdisciplinary research among other robotics &automation fields• NIST benefits– Provide a test bed for new standards and performance metrics– Provide ties to both researchers and industry
Capital Science 2008<strong>Virtual</strong> <strong>Manufacturing</strong> <strong>Automation</strong><strong>Competition</strong> (VMAC)• Advancing Robotic Research through an <strong>Open</strong><strong>Source</strong> High-Fidelity Simulation Framework and<strong>Competition</strong>– PIs: Stephen Balakirsky, Raj Madhavan, Chris Scrapper– <strong>Manufacturing</strong> <strong>Automation</strong> Regional <strong>Competition</strong>– One of the 10 proposals that was funded out of 33submitted• Joint NIST, IEEE Robotics and <strong>Automation</strong>Society effort• 7 teams selected– Morgan State University, George WashingtonUniversity, University of Maryland EasternShore, George Mason University & HoodCollege– Faculty: 7 Students: 11• Tutorial and workshop held at NIST in Oct’07• Follow-up workshop held at Hood College inFeb’08
Capital Science 2008Accepted TeamsUniversity (Dept.) Faculty Student(s) EmailGMU (CS) 1. Zoran Duric 1. Eugene Yu zduric@cs.gmu.eduGWU (CS) 2. Rahul Simha 2. Darby Thompson3. Alex StefanovskiGWU (MAE)UMES (EAS)Hood College (CS)Morgan State (ME)James D. Lee3. Ali Eydgahi4. Payam Matin5. George Dimitoglou6. Xinlian LiuAll participating teams received:Xiaowei Zeng4. Mark Bivens5. Chris Epps6. Lee Long7. Brandon Burger8. Kristopher Reese9. Eric Walton7. Keith Hargrove 10. Therese <strong>An</strong>deme11. Kashun Davis• Linux Machines with USARSim & MOAST• A Dell Computer & Monitor• Mouse, Keyboard & Joystick• Unreal Game Enginesimha@gwu.eduxwzeng@gwu.eduaeydgahi@umes.edudimitoglou@hood.eduhargrove@eng.morgan.edu
• Teams will be composed of1 - 3 autonomous unitloader vehicles• Task will be factorylogistics– Move packages from adistribution point to severaldispersed locations– Multiple paths to destination,some large enough for two-waytraffic, others only large enoughfor a single vehicle– Largest number of correctlydelivered packages wins• Task decomposition– Path following– Docking with roller tables– Route planning– Traffic managementCapital Science 2008<strong>Competition</strong> Basics
Capital Science 2008Software Infrastructure• USARSim – Developedas a NSF fundedresearch tool by CMUand UPitt– Now an open sourceproject managed by NIST– Internationaldevelopment community– Physics based simulation– Provides the embodimentand environment for thecompetition
Capital Science 2008Scoring Metrics• <strong>Competition</strong> consists of “main-event” as wellas “best-in-class” competitions• Main-event scoring– Points awarded for successful pick-up anddelivery of packages– Points subtracted for dropped packages andcollisions, and incorrect deliveries
Capital Science 2008Best-in-class Path Following• Robot must drive down aseries of passageways atspecified velocity• Each passagewaynarrower then the last• Points awarded fordistance traveled• Points subtracted fordeviations over boundaryand in velocity• Test run with and withoutground truth• Green lines show commandedpath and passageway boundary• Red line is actual robot path
Capital Science 2008Best-in-class Map Building• Technology needed for initial system setupand during normal operation• No ground truth• Scoring leverage RoboCup– Metric quality– Skeleton quality– Multi-vehicle fusion
Capital Science 2008Best-in-class Docking• Team must dock AGVwith loading station– Tested over constellation ofstarting locations– Free space formaneuvering reduced aftereach series of runs– Ground truth provided• Points awarded for successful dock– Time and collisions affect score
Capital Science 2008Beyond this <strong>Competition</strong> …• Finalists of the competition willdemo their results at ICRA 2008 inconjunction with the ICRA RobotChallenge• ICRA 2008 Robot <strong>Competition</strong>Workshop• Special session at PerMIS onVMAC competition• <strong>Competition</strong> at ICRA 2009 (Kobe,Japan)• NIST– Implementation on real robots infactory settings– Expand range of robots and metricsemployed in the competition
Capital Science 2008Timeline• Final <strong>Competition</strong>: April18 th 2008 (a month beforeICRA’08)• Present Research &Outcomes– Special Session at thePerformance Metrics forIntelligent SystemsWorkshop (Raj Madhavan:Program Chair): August’08– Follow-up <strong>Competition</strong>:September’08