Abstract
In the last fifteen years, much interest has been focused on the deployment of large teams of autonomous robots for applications such as environmental monitoring, surveillance and reconnaissance, and automated parts inspection for manufacturing. The objective is to leverage the team’s inherent redundancy to simultaneously cover wide regions and achieve massive parallelization in task execution while remaining robust to individual failures. Despite recent successes, significant challenges remain, in part, due to the difficulties associated with managing and coordinating the various redundancies that exist in a large team of homogeneous agents. In this chapter, we present an ensemble approach towards the design of distributed control and communication strategies for the dynamic allocation of a team of robots to a set of tasks. This approach uses a class of stochastic hybrid systems to model the robot team dynamics as a continuous-time Markov jump process. The main advantage is a lower-dimensional representation of the team dynamics that is amenable to system-level analysis of the team’s performance in the presence of task differentiation. We show how such analysis can be further used to design and optimize individual robot control policies through simulations and experimental validation.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Berman, S., Halasz, A., Hsieh, M.A., Kumar, V.: Navigation-based optimization of stochastic deployment strategies for a robot swarm to multiple sites. In: Proc. of the 47th IEEE Conference on Decision and Control, Cancun, Mexico (2008)
Berman, S., Halasz, A., Hsieh, M.A., Kumar, V.: Optimized stochastic policies for task allocation in swarms of robots. IEEE Transactions on Robotics 25(4), 927–937 (2009)
Chen, J., Latchman, H.: Frequency sweeping tests for stability independent of delay. IEEE Transactions on Automatic Control 40(9), 1640–1645 (1995), doi:10.1109/9.412637
Dahl, T.S., Mataric̀, M.J., Sukhatme, G.S.: A machine learning method for improving task allocation in distributed multi-robot transportation. In: Braha, D., Minai, A., Bar-Yam, Y. (eds.) Understanding Complex Systems: Science Meets Technology, pp. 307–337. Springer, Berlin (2006)
Dias, M.B.: Traderbots: A new paradigm for robust and efficient multirobot coordination in dynamic environments. PhD thesis, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA (2004)
Dias, M.B., Zlot, R.M., Kalra, N., Stentz, A.T.: Market-based multirobot coordination: a survey and analysis. Proceedings of the IEEE 94(7), 1257–1270 (2006)
Gerkey, B.P., Matarić, M.J.: Sold!: Auction methods for multi-robot control. IEEE Transactions on Robotics & Automation 18(5), 758–768 (2002)
Gerkey, B.P., Matarić, M.J.: A formal framework for the study of task allocation in multi-robot systems. International Journal of Robotics Research 23(9), 939–954 (2004)
Golfarelli, M., Maio, D., Rizzi, S.: Multi-agent path planning based on task-swap negotiation. In: Proceedings of the 16th UK Planning and Scheduling SIG Workshop, PlanSIG, Durham, England (1997)
Guerrero, J., Oliver, G.: Multi-robot task allocation strategies using auction-like mechanisms. In: Artificial Research and Development, Frontiers in Artificial Intelligence and Applications, vol. 100, pp. 111–122. IOS Press (2003)
Halasz, A., Hsieh, M.A., Berman, S., Kumar, V.: Dynamic redistribution of a swarm of robots among multiple sites. In: Proceedings of the Conference on Intelligent Robot Systems (IROS 2007), San Diego, CA, pp. 2320–2325 (2007)
Hespanha, J.P.: Moment closure for biochemical networks. In: Proc. of the Third Int. Symp. on Control, Communications and Signal Processing (2008)
Hsieh, M.A., Halasz, A., Berman, S., Kumar, V.: Biologically inspired redistribution of a swarm of robots among multiple sites. Swarm Intelligence (2008)
Hsieh, M.A., Halasz, A., Cubuk, E.D., Schoenholz, S., Martinoli, A.: Specialization as an optimal strategy under varying external conditions. In: Accepted the International Conference on Robotics and Automation, ICRA 2007, Kobe-Japan (2009)
Jones, E.G., Browning, B., Dias, M.B., Argall, B., Veloso, M., Stentz, A.T.: Dynamically formed heterogeneous robot teams performing tightly-coordinated tasks. In: Proceedings of the 2006 IEEE International Conference on Robotics and Automation (ICRA 2006), pp. 570–575. IEEE, Los Alamitos (2006)
Jones, E.G., Dias, M.B., Stentz, A.: Learning-enhanced market-based task allocation for oversubscribed domains. In: Proceedings of the Conference on Intelligent Robot Systems (IROS 2007), pp. 2308–2313. IEEE, Los Alamitos (2007)
Klavins, E.: Proportional-integral control of stochastic gene regulatory networks. In: Proc. of the 2010 IEEE Conf. on Decision and Control (CDC 2010), Atlanta, GA, USA (2010)
Lerman, K., Jones, C., Galstyan, A., Matarić, M.J.: Analysis of dynamic task allocation in multi-robot systems. International Journal of Robotics Research (2006)
Lin, L., Zheng, Z.: Combinatorial bids based multi-robot task allocation method. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation (ICRA 2005), pp. 1145–1150. IEEE, Los Alamitos (2005)
Martinoli, A., Easton, K., Agassounon, W.: Modeling of swarm robotic systems: a case study in collaborative distributed manipulation. International Journal of Robotics Research: Special Issue on Experimental Robotics 23(4-5), 415–436 (2004)
Mather, T.W., Hsieh, M.A.: Distributed filtering for time-delayed deployment to multiple sites (best paper award winner). In: 10th International Symposium on Distributed Autonomous Robotics Systems (DARS 2010), Lausanne, Switzerland (November 2010)
Mather, T.W., Hsieh, M.A.: Analysis of stochastic deployment policies with time delays for robot ensembles. International Journal of Robotics Research: Special Issue on Stochasticity in Robotics & Biological Systems, Part 1 30(5) (2011)
Mather, T.W., Hsieh, M.A.: Distributed robot ensemble control for deployment to multiple sites. In: 2011 Robotics: Science and Systems, Los Angeles, CA USA (2011)
USARSim, Unified system for automation and robot simulation (2005), http://usarsim.sourceforge.net
Vail, D., Veloso, M.: Multi-robot dynamic role assignment and coordination through shared potential fields. In: Schultz, A., Parker, L., Schneider, F. (eds.) Multi-Robot Systems, pp. 87–98. Kluwer (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Hsieh, M.A., Mather, T.W. (2013). Robustness in the Presence of Task Differentiation in Robot Ensembles. In: Milutinović, D., Rosen, J. (eds) Redundancy in Robot Manipulators and Multi-Robot Systems. Lecture Notes in Electrical Engineering, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33971-4_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-33971-4_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33970-7
Online ISBN: 978-3-642-33971-4
eBook Packages: EngineeringEngineering (R0)