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Designing Robot Competitions Designing Robot Competitions That Promote AI Solutions:That Promote AI Solutions:Lessons Learned Competing and DesigningLessons Learned Competing and Designing

Jeffrey R. CroxellJeffrey R. Croxell

Ross MeadRoss Mead

Jerry B. WeinbergJerry B. Weinberg

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IntroductionIntroduction• Robotics competitions are an excellent educational tool at the Robotics competitions are an excellent educational tool at the

middle school, high school, and university levelsmiddle school, high school, and university levels

• GGameplayameplay of competition impacts emphasis for robot designs... of competition impacts emphasis for robot designs...– Rouse 2001Rouse 2001

• DARPA, RoboCup, and AAAI competitions…DARPA, RoboCup, and AAAI competitions…– emphasize outstanding research issues in AIemphasize outstanding research issues in AI– can be cost prohibitivecan be cost prohibitive– requires significant human labor and team sizerequires significant human labor and team size

• Other competitions typically require little use of AI…Other competitions typically require little use of AI…– open-loopopen-loop designs designs

• Large gap between these typesLarge gap between these types

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IntroductionIntroduction

• Small-scale competitions can still promote Small-scale competitions can still promote AI solutions and AI solutions and closed-loopclosed-loop designs… designs…– smaller physical sizesmaller physical size– less costlyless costly– easier to handleeasier to handle

• Help bridge the gap from simpler to more Help bridge the gap from simpler to more advanced competitionsadvanced competitions

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Our DesignOur Design• General purposeGeneral purpose

• Lynxmotion…Lynxmotion…– 4WD14WD1– 5 DoF arm5 DoF arm

• XBCXBC

• Light sensorsLight sensors

• SonarSonar

• IR rangefindersIR rangefinders

• CameraCamera

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IEEE Region 5 CompetitionIEEE Region 5 Competition

• Mini warehouseMini warehouse

• Automated sorterAutomated sorter

• 4 colored cans placed 4 colored cans placed at random locationsat random locations

• Sort into proper roomSort into proper room

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2006 Beyond Botball2006 Beyond Botball

• Head-to-headHead-to-head

• Remove “toxic waste”Remove “toxic waste”

• Save Billy and Betty Save Billy and Betty BotguyBotguy

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Competing DesignsCompeting Designs

• Highly engineered Highly engineered designsdesigns

• Movement based on little-Movement based on little-to-no sensor feedback…to-no sensor feedback…– no obstacle avoidanceno obstacle avoidance

• Grabbed objects from Grabbed objects from known locations…known locations…– no searchingno searching

• Simple and effectiveSimple and effective

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Competition ResultsCompetition Results

• IEEE…IEEE…– finalists recognized dominant strategyfinalists recognized dominant strategy

• Beyond Botball…Beyond Botball…– highly engineered design highly engineered design →→ faster and more effective faster and more effective

• Winner’s circles of these competitions consisted Winner’s circles of these competitions consisted primarily of robots with little intelligence…primarily of robots with little intelligence…– more intelligent robots may be overkill for these more intelligent robots may be overkill for these

competitionscompetitions

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Designer’s PerspectiveDesigner’s Perspective

• Annual SIUE Robotics CompetitionsAnnual SIUE Robotics Competitions

(based on design in Martin 2001)

roboti.cs.siue.edu

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Lessons LearnedLessons Learned

• Given game specifics, teams assume…Given game specifics, teams assume…– known layout of the arenaknown layout of the arena

• no mapping necessaryno mapping necessary

– locations of objects and goalslocations of objects and goals• no searching necessaryno searching necessary

– series of actions to achieve objectivesseries of actions to achieve objectives• no localization or motion planning necessaryno localization or motion planning necessary

– static arena statestatic arena state• closed-world assumptionclosed-world assumption ( (Murphy 2000Murphy 2000))

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““Real Robots Don’t Drive Straight”Real Robots Don’t Drive Straight”

“… “… students are unlikely to develop students are unlikely to develop feedback-based approaches in their feedback-based approaches in their designs of mobile robots in contest designs of mobile robots in contest

events.” — events.” — Martin 2007Martin 2007

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Emphasizing AI SolutionsEmphasizing AI Solutions

• Promote the use of closed-loop designs…Promote the use of closed-loop designs…– degrees of uncertainty must be included in the rules of the gamedegrees of uncertainty must be included in the rules of the game

• Encourage planning and re-planning based on physical Encourage planning and re-planning based on physical interactions…interactions…– with the environmentwith the environment– with objectswith objects– with other robotswith other robots

• Intelligent decision-making takes time!Intelligent decision-making takes time!– not much is offered by current competitionsnot much is offered by current competitions

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Opportunities in MappingOpportunities in Mapping

• Eliminate the closed-world assumption…Eliminate the closed-world assumption…– do not specify all characteristics of the field of playdo not specify all characteristics of the field of play

• Environment can be obstructive and interactive…Environment can be obstructive and interactive…– present robots with interesting situations and opportunitiespresent robots with interesting situations and opportunities

RoboFestwww.robofest.net moveable wooden barriermoveable wooden barrier

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Opportunities in LocalizationOpportunities in Localization

• Require robots to traverse Require robots to traverse much of the arena board…much of the arena board…– dead reckoning is adequate dead reckoning is adequate

for current competitionsfor current competitions– error accumulates quicklyerror accumulates quickly

• Provide a means for Provide a means for determining spatial position determining spatial position and orientation while and orientation while navigating the world…navigating the world…– physical and visual landmarksphysical and visual landmarks

FireBot Challengeroboti.cs.siue.edu

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Opportunities in Object RecognitionOpportunities in Object Recognition

• Place game objectives at Place game objectives at unspecified locations…unspecified locations…– if the locations of these if the locations of these

objects are given, there is objects are given, there is no need for a search!no need for a search!

– encourages the use of encourages the use of sensors to locate and sensors to locate and approach game objectsapproach game objects

RoboSoccer Shootout!roboti.cs.siue.edu

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Opportunities inOpportunities inNavigation and PlanningNavigation and Planning

• Unknown locations/order of objectives…Unknown locations/order of objectives…– difficult to rely on a fixed navigational strategydifficult to rely on a fixed navigational strategy

• Navigation involves obstacle avoidanceNavigation involves obstacle avoidance

• More complex interactions with objects…More complex interactions with objects…– planning for object manipulationplanning for object manipulation

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Opportunities in InteractionsOpportunities in Interactions

• Include obstacles!Include obstacles!– expected or unexpectedexpected or unexpected– traversable or obstructivetraversable or obstructive– game board itselfgame board itself

• Allow for or encourage Allow for or encourage nondestructivenondestructive interactions between interactions between competing robots…competing robots…– promotes use of sensory promotes use of sensory

feedback to predict, avoid, feedback to predict, avoid, or handle collisionsor handle collisions

Beyond Botball 2006www.botball.org

FireBot Challengeroboti.cs.siue.edu

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Opportunities in TimeOpportunities in Time

• Sensing the environment and making Sensing the environment and making decisions based on this feedback is a decisions based on this feedback is a time-consuming process…time-consuming process…– constrains AI-type strategies the most!constrains AI-type strategies the most!

• Provide enough time for robots to examine Provide enough time for robots to examine surroundings and calculate responsessurroundings and calculate responses

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An ExampleAn Example

• Search-and-rescue…Search-and-rescue…– 10’x10’ arena representing an 10’x10’ arena representing an

earthquake-damaged earthquake-damaged warehousewarehouse

• ““Blueprint” is given…Blueprint” is given…– unknown conditions insideunknown conditions inside

• Robots explore the arena and Robots explore the arena and search for victims…search for victims…– all wearing red uniformsall wearing red uniforms

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An ExampleAn Example

• As the robot traverses the As the robot traverses the arena, it must sense objects…arena, it must sense objects…– avoid obstaclesavoid obstacles– approach, confirm (signal), approach, confirm (signal),

and map victims foundand map victims found

• Dead reckoning is primary Dead reckoning is primary method of localization…method of localization…– known colored landmarks and known colored landmarks and

tone emitters for recalibrationtone emitters for recalibration

• 35º incline to second floor35º incline to second floor

• 15 minute time period15 minute time period

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ConclusionsConclusions• Rules must encourage AI Rules must encourage AI

solutionssolutions

• Environment should reward Environment should reward sensory reaction and high-level sensory reaction and high-level decision-makingdecision-making

• Important elements:Important elements:– unspecified dimensionsunspecified dimensions– random placementrandom placement– time constraintstime constraints

• Techniques utilized help provide Techniques utilized help provide an introduction to higher-level an introduction to higher-level concepts and challengesconcepts and challenges

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ReferencesReferences• Arkin, R. 1998. Arkin, R. 1998. Behavior-Based RoboticsBehavior-Based Robotics. The MIT . The MIT

Press.Press.

• Kumar, D. and Meeden, L. 1998. “A Robot Kumar, D. and Meeden, L. 1998. “A Robot Laboratory for Teaching Artificial Intelligence” in Laboratory for Teaching Artificial Intelligence” in Proceedings of the Twenty-ninth SIGCSE Technical Proceedings of the Twenty-ninth SIGCSE Technical Symposium on Computer Science EducationSymposium on Computer Science Education , D. , D. Joyce, ed. ), Volume 30, Number 1, Pages 341--Joyce, ed. ), Volume 30, Number 1, Pages 341--344, ACM Press, March 1998.344, ACM Press, March 1998.

• Laird, J.E. and van Lent, M. 2001. “Computer Laird, J.E. and van Lent, M. 2001. “Computer Game Tutorial”, Tutorial Program at the Game Tutorial”, Tutorial Program at the Seventeeth Seventeeth International Joint Conference on Artificial International Joint Conference on Artificial IntelligenceIntelligence, Seattle, WA., Seattle, WA.

• Martin, F.G. 2001. Martin, F.G. 2001. Robotic Explorations: A Hands-Robotic Explorations: A Hands-On Introduction to EngineeringOn Introduction to Engineering, Prentice Hall, , Prentice Hall, Upper Saddle River, NJ.Upper Saddle River, NJ.

• Martin, F.G. 2007. “Real Robots Don’t Drive Martin, F.G. 2007. “Real Robots Don’t Drive Straight” in Straight” in Robots and Robot Venues: Resources Robots and Robot Venues: Resources for AI Education: Papers from the AAAI Spring for AI Education: Papers from the AAAI Spring SymposiumSymposium, March 2007., March 2007.

• Mayer, G., Weinberg, J.B., and Yu, X., 2004. Mayer, G., Weinberg, J.B., and Yu, X., 2004. “Teaching Deliberative Navigation Using the LEGO “Teaching Deliberative Navigation Using the LEGO RCX and Standard LEGO Components”, RCX and Standard LEGO Components”, Accessible Hands on Artificial Intelligence and Accessible Hands on Artificial Intelligence and Robotics Education: Working Papers of the 2004 Robotics Education: Working Papers of the 2004 AAAI Spring Symposium SeriesAAAI Spring Symposium Series, March 2004., March 2004.

• Miller, D. and Stein, C. 2000. “‘So That’s What Pi is Miller, D. and Stein, C. 2000. “‘So That’s What Pi is For!’ and Other Educational Epiphanies from Hands For!’ and Other Educational Epiphanies from Hands on Robotics”, on Robotics”, Robots for Kids: Exploring New Robots for Kids: Exploring New Technologies for LearningTechnologies for Learning, A. Druin and J. Hendler, , A. Druin and J. Hendler, (Eds.), Morgan Kaufmann, pp. 220-243.(Eds.), Morgan Kaufmann, pp. 220-243.

• Murphy, R. 2000. Murphy, R. 2000. An Introduction to AI RoboticsAn Introduction to AI Robotics. . The MIT Press. The MIT Press.

• Rouse, R. 2001. Rouse, R. 2001. Game Design: Theory and Game Design: Theory and PracticePractice. Wordware Publishing, Inc., Plano, TX.. Wordware Publishing, Inc., Plano, TX.

• Weinberg, J.B.,  W. White, C. Karacal, G. Engel, & Weinberg, J.B.,  W. White, C. Karacal, G. Engel, & A. Hu, “Multidisciplinary Teamwork in a Robotics A. Hu, “Multidisciplinary Teamwork in a Robotics Course”, Course”, The 36th ACM Technical Symposium on The 36th ACM Technical Symposium on Computer Science Education,Computer Science Education, February 2005, pp. February 2005, pp. 446-450.446-450.

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