Presentation on theme: "Market-Based Coordination of Recharging Robots"— Presentation transcript:
1Market-Based Coordination of Recharging Robots Victor MarmolSchool of Computer ScienceSenior ThesisAdvisor:M. Bernardine Dias, Ph.D.Robotics InstituteMentor:Balajee Kannan, Ph.D.Robotics Institute
2Autonomous Recharging Necessary for any group of mobile robots that are to be effective beyond a short amount of timeRobots can run for weeks, months, yearsMobile and static recharging units allow a group of worker robots to recharge when necessaryMobile recharger docking with a worker.Real system (left) CAD model (right)
3Related Work Most existing systems don’t implement recharging Most existing approaches are threshold-based and make decisions utilizing only the current stateBattery voltage threshold [2, Silverman et al. 2002][8, Silverman et al. 2003][12, Munoz et al. 2002][13, Munoz et al. 2002]Time threshold [5, Austin et al. 2001]Distance threshold [4, Waverla at al. 2008][7, Waverla et al. 2007]Most current systems aren’t charge-awareNo existing strategy for coordinating multiple worker robots and a recharging unit
4Our ApproachDesign and develop a market-based distributed system for planning and coordinationGive each robot charge-awarenessEnhance system to include mobile rechargersMobile recharging agent’s docking armGUI integrating map and robot control
5Market-Based SystemsUses a simulated economy to trade tasks between robots based on their costsCost is defined by a set of cost functionsAdvantages:DistributedFault tolerantScalableTaskAn auction for a task with two bidding robots. Arrows are bids,green arrows are winning bids. Cost metric is distance.
6Charge-aware schedule Charge-AwarenessRobots estimate their remaining operational timeWorkers bid on work tasks to insert into their schedulesRecharging tasks inserted to create balanced schedulesSchedules are optimized to minimize distance traveledWorkers assume no mobile rechargers for initial estimateTaskTaskTaskTaskCharge-AwareHomeTaskTaskExisting scheduleCharge-aware schedule
7Schedule with mobile recharging Mobile RechargersGoal: maximize work done by worker robotsWorkers auction off recharging tasksMobile rechargers bid on recharging tasks with rendezvous points along the worker’s pathTaskTaskRechargeTaskSchedule with mobile recharging
8Evaluation: Distance Ran all strategies on a schedule of 50 tasks StrategyDistance GainsCharge-AwareMobile RechargerInfinite battery-1.37 (-0.08%)-0.96 (-0.56%)Battery threshold15.89 (9.29%)16.30 (9.55%)Distance threshold15.76 (9.21%)16.17 (9.48%)Charge-aware-0.41 (0.24%)Mobile recharger-0.41 (-0.24%
9Evaluation: Time Ran all strategies on a schedule of 50 tasks Two methods for calculating recharging timeMethod 1: Constant time to rechargeMethod 2: Proportional to amount of charge requiredTime GainsCharge-AwareMobile RechargerStrategyMethod #1Method #2Infinite battery(-5.24%)(-65.73%)(-3.74%)(-62.43%)Battery threshold52.00 (5.13%)(4.77%)67.79 (6.80%)(14.49%)Distance threshold102 (10.07%)9.50 (0.34%)(11.81%)(9.99%)Charge-aware-15.79 (1.59%)(9.62%)Mobile recharger(-1.56%)(-8.77%)
10Evaluation: Scalability (Distance) Ran all strategies on schedules of increasing sizeOur strategies consistently outperform current approaches
11Conclusion & Future work Our strategies represent an advancement in the state of the art for autonomous rechargingPlanning and coordination in autonomous recharging greatly enhances the amount of work performed by mobile robotsFuture WorkExtend to larger teamsMore workersMore mobile rechargersMake mobile rechargers charge-aware
12Acknowledgements M. Bernardine Dias, Ph.D. and Balajee Kannan, Ph.D. Jimmy Bourne, Sairam Yamanoor, M. Freddie Dias, and Nisarg KothariEveryone in the rCommerce groupPart of the rCommerce group
13ReferencesSeungjun Oh, A. Z. & K. Taylor (2000). Autonomous battery recharging for indoor mobile robots, in the proceedings of Australian Conference on Robotics and Automation (ACRA2000).Silverman, M.C ; Nies, D ; Jung, B & Sukhatme, G.S (2002). Staying alive: A docking station for autonomous robot recharging, in IEEE Intl. Conf. on Robotics and Automation, 2002Kottas, A., Drenner, A., and Papanikolopoulos, N Intelligent power management: promoting power-consciousness in teams of mobile robots. In Proceedings of the 2009 IEEE international Conference on Robotics and Automation (Kobe, Japan, May , 2009). IEEE Press, Piscataway, NJ,J. Wawerla and R. T. Vaughan. Optimal robot recharging strategies for time discounted labour. In Proc. of the 11th Int. Conf. on the Simulation and Synthesis of Living Systems, 2008.D. J. Austin, L. Fletcher, and A. Zelinsky, .Mobile robotics in the long term,. in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), OctLitus, Y., Vaughan, R. T., and Zebrowski, P. (2007). The frugal feeding problem: Energy-efficient, multi-robot, multi-place rendezvous. In Proceedings of the IEEE International Conference on Robotics and Automation.Wawerla, J. and Vaughan, R. T. (2007). Near-optimal mobile robot recharging with the rate-maximizing forager. In Proceedings of the European Conference on Artificial Life.M. Silverman, B. Jung, D. Nies, G. Sukhatme. “Staying Alive Longer: Autonomous Robot Recharging Put to the Test.” Center for Robotics and Embedded Systems (CRES) Technical Report CRES University of Southern California, 2003.Alex Couture-Beil and Richard T. Vaughan. Adaptive mobile charging stations for multi-robot systems. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS'09).St. Loius, MO, October 2009.Zebrowski, P ; Vaughan, R (2005). Recharging Robot Teams: A Tanker Approach, International Conference on Advanced Robotics (ICAR'05), Seattle, Washington, July 18th-20th, 2005.
14ReferencesYaroslav Litus, Pawel Zebrowski, and Richard T. Vaughan. A distributed heuristic for energy-efficient multi-robot multi-place rendezvous. IEEE Transactions on Robotics, 25(1): , 2009.Munoz A., Sempe F., and Drogoul A. (2002). Sharing a Charging Station in Collective Robotics.Sempé F., Muñoz A., Drogoul A. “Autonomous Robots Sharing a Charging Station with no Communication: a Case Study.” Proceedings of the 6th International Symposium on Distributed Autonomous Robotic Systems (DARS'02). June 2002.M. B. Dias, “Traderbots: A new paradigm for robust and efficient multirobot coordination in dynamic environments,” Ph.D. dissertation, Robotics Institute, Carnegie Mellon University, January 2004.TraderBots User’s Guide. Carnegie Mellon University, National Robotics Engineering Center. August 1, 2008.Flinn, J., Satyanarayanan, M. Energy-aware Adaptation for Mobile Applications. In Proceedings of the 17th ACM Symposium on Operating Systems and Principles. Kiawah Island, SC, December, 1999.McFarland, D. & Spier, E. (1997). Basic cycles, utility and opportunism in self-sufficient robots. Robotics and Autonomous Systems, 20,Birk A. (1997) Autonomous Recharging of Mobile Robots. In: Proceedings of the 30th International Sysposium on Automative Technology and Automation. Isata PressNgo, T. D., Raposo, H., Schioler, H., Being Sociable: Multirobots with Self-sustained Energy, Proceedings of the 15th IEEE Mediterranean Conference on Control and Automation, Athens, Greece, July, 2007