A comparison of deterministic and stochastic approaches for allocating spatially dependent tasks in micro-aerial vehicle collectives

IEEE International Conference on Intelligent Robots and Systems

Volumn , Issue , 2012, Pages 793-800

  Dantu, Karthik ^a   Berman, Spring ^b   Kate, Bryan ^a   Nagpal, Radhika ^a  

^a HARVARD UNIVERSITY   (United States)

^b Arizona State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CROP FIELDS; DEPENDENT TASKS; DETERMINISTIC APPROACH; FEASIBLE ALTERNATIVES; LARGE POPULATION; MICRO AERIAL VEHICLE; REALISTIC CONDITIONS; REGION-BASED; RESOURCE-CONSTRAINED; ROBOT LOCALIZATION; ROBOT NAVIGATION; STOCHASTIC APPROACH; TASK ALLOCATION;

INTELLIGENT SYSTEMS; NAVIGATION; ROBOT APPLICATIONS; ROBOTICS; STOCHASTIC SYSTEMS;

ROBOTS;

EID: 84872281743     PISSN: 21530858     EISSN: 21530866     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2012.6386233     Document Type: Conference Paper

References (35)

1. W. Agassounon and A. Martinoli. Efficiency and robustness of threshold-based distributed allocation algorithms in multi-agent systems. In Proc. First Int'l. Joint Conf. on Autonomous Agents and Multi-Agent Systems (AAMAS), pages 1090-1097, 2002.
2. S. Berman, Á . Halász, M. A. Hsieh, and V. Kumar. Optimized stochastic policies for task allocation in swarms of robots. IEEE Trans. Robotics, 25(4):927-937, Aug. 2009.
3. S. Berman, V. Kumar, and R. Nagpal. Design of control policies for spatially inhomogeneous robot swarms with application to commercial pollination. In Int'l. Conf. Robotics and Automation (ICRA), pages 378-385, 2011.
4. S. Berman, R. Nagpal, and Á . Halász. Optimization of stochastic strategies for spatially inhomogeneous robot swarms: A case study in commercial pollination. In Int'l. Conf. Intelligent Robots and Systems (IROS), pages 3923-3930, 2011.
5. H.-L. Choi, L. Brunet, and J. P. How. Consensus-based decentralized auctions for robust task allocation. IEEE Transactions on Robotics, 25(4):912-926, August 2009.
6. N. Correll. Parameter estimation and optimal control of swarm-robotic systems: A case study in distributed task allocation. In Int'l. Conf. Robotics and Automation (ICRA), pages 3302-3307, 2008.
7. K. Dantu, B. Kate, J. Waterman, P. Bailis, and M. Welsh. Programming micro-aerial vehicle swarms with Karma. In Proc. 9th ACM Conference on Embedded Networked Sensor Systems, SenSys'11, pages 121-134, New York, NY, 2011. ACM.
8. M. B. Dias, R. Zlot, N. Kalra, and A. Stentz. Market-based multirobot coordination: A survey and analysis. Proceedings of the IEEE, 94(7):1257-1270, July 2006.
9. B. Gerkey and M. Matarić. A formal analysis and taxonomy of task allocation in multi-robot systems. Int'l. J. of Robotics Research, 23(9):939-954, 2004.
10. D. T. Gillespie. Information flow, opinion polling and collective intelligence in house-hunting social insects. Phil. Trans. Roy. Soc. London, B(357):1567-1584, 2002.
11. H. Hamann and H. Wörn. A framework of space-time continuous models for algorithm design in swarm robotics. Swarm Intelligence, 2(2-4):209-239, 2008.
12. W. Hundsdorfer and J. G. Verwer. Numerical Solution of Time- Dependent Advection-Diffusion-Reaction Equations, volume 33 of Springer Series in Computational Mathematics. Springer, Berlin, 2003.
13. M. Karpelson, J. P. Whitney, G.-Y. Wei, and R. J. Wood. Energetics of flapping-wing robotic insects: Towards autonomous hovering flight. In Proc. IEEE/RSJ Int'l. Conf. on Intelligent Robots and Systems (IROS), pages 1630-1637, Oct. 2010.
14. B. Kate, J. Waterman, K. Dantu, and M. Welsh. Simbeeotic: A simulator and testbed for micro-aerial vehicle swarm experiments. In Proc. 11th ACM/IEEE Conf. on Information Processing in Sensor Networks, IPSN-SPOTS '12. IEEE/ACM, April 2012.
15. S. Koppal, I. Gkioulekas, G. Barrows, and T. Zickler. Wide-angle micro sensors for vision on a tight budget. In Proc. IEEE Conf. on Computer Vision and Pattern Recog. (CVPR), pages 361-368, 2011.
16. G. A. Korsah. Exploring bounded optimal coordination for heterogeneous teams with cross-schedule dependencies. PhD thesis, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 2011.
17. M. J. B. Krieger, J.-B. Billeter, and L. Keller. Ant-like task allocation and recruitment in cooperative robots. Nature, 406:992-995, 2000.
18. T. H. Labella, M. Dorigo, and J.-L. Deneubourg. Division of labor in a group of robots inspired by ants' foraging behavior. ACM Trans. Auton. Adapt. Syst., 1(1):4-25, 2006.
19. M. G. Lagoudakis, E. Markakis, D. Kempe, P. Keskinocak, A. Kleywegt, S. Koenig, C. Tovey, A. Meyerson, and S. Jain. Auction-based multi-robot routing. In In Robotics: Science and Systems, pages 343-350, 2005.
20. R. J. Leveque. Finite-Volume Methods for Hyperbolic Problems. Cambridge Univ. Press, 2004.
21. W. Liu and A. F. T. Winfield. Modeling and optimization of adaptive foraging in swarm robotic systems. Int'l. J. of Robotics Research, 29(14):1743-1760, 2010.
22. N. Michael, J. Fink, S. Loizou, and V. Kumar. Architecture, abstractions, and algorithms for controlling large teams of robots: Experimental testbed and results. Int'l. Symposium of Robotics Research (ISRR), 2007.
23. D. Milutinovic and P. Lima. Modeling and optimal centralized control of a large-size robotic population. IEEE Trans. Robotics, 22(6):1280-1285, 2006.
24. L. Odhner and H. Asada. Stochastic recruitment control of large ensemble systems with limited feedback. ASME J. Dyn. Sys. Meas. Control, 132(4):041008-1-041008-9, 2010.
25. H. S. of Engineering and A. Sciences. RoboBees: A Convergence of Body, Brain, and Colony, 2012. http://robobees.seas.harvard.edu/.
26. A. Powell, W. A. D. Jr., and D. G. Himelrick. Commercial blueberry production guide for Alabama, 2002. Alabama Cooperative Extension System, ANR-904.
27. A. Prorok, N. Correll, and A. Martinoli. Multi-level spatial modeling for stochastic distributed robotic systems. Int'l. J. of Robotics Research, 30(5):574-589, 2011.
28. M. Rubenstein, C. Ahler, and R. Nagpal. Kilobot: A low cost scalable robot system for collective behaviors. In Proc. IEEE Int'l. Conf. on Robotics and Automation (ICRA), 2012.
29. O. Shehory and S. Kraus. Methods for task allocation via agent coalition formation. Artificial Intelligence, 101:165-200, 1998.
30. P. S. Sreetharan and R. J. Wood. Passive torque regulation in an underactuated flapping wing robotic insect. Autonomous Robots, 31(2-3):225-234, Oct. 2011.
31. L. Vig and J. Adams. Multi-robot coalition formation. IEEE Trans. on Robotics, 22(4):637-649, 2006.
32. L. Vig and J. Adams. Coalition formation: From software agents to robots. J. Intellig. and Robotic Syst., 50(1):85-118, 2007.
33. R. J. Wood. The first takeoff of a biologically inspired at-scale robotic insect. IEEE Transactions on Robotics, 24(2):341-347, April 2008.
34. R. J. Wood. Fly, robot, fly. Spectrum, IEEE, 45(3):25-29, Mar. 2008.
35. R. Zlot. An auction-based approach to complex task allocation for multirobot teams. PhD thesis, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 2006.