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Erschienen in:
A Bearing-Only Pattern Formation Algorithm for Swarm Robotics Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Dynamic Task Partitioning for Foraging Robot Swarms

verfasst von : Edgar Buchanan, Andrew Pomfret, Jon Timmis

Erschienen in: Swarm Intelligence

Verlag: Springer International Publishing

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Abstract

Dead reckoning error is a common problem in robotics that can be caused by multiple factors related to sensors or actuators. These errors potentially cause landmarks recorded by a robot to appear in a different location with respect to the actual position of the object. In a foraging scenario with a swarm of robots, this error will ultimately lead to the robots being unable to return successfully to the food source. In order to address this issue, we propose a computationally low-cost finite state machine strategy with which robots divide the total travelling distance into a variable number of segments, thus decreasing accumulated dead-reckoning error. The distance travelled by each robot changes according to the success and failure of exploration. Our approach is more flexible than using a previously used fixed size approach for the travel distance, thus allowing swarms greater flexibility and scaling to larger areas of operation.

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Vorheriges Kapitel Design and Analysis of Proximate Mechanisms for Cooperative Transport in Real Robots
Nächstes Kapitel Human-Robot Swarm Interaction with Limited Situational Awareness
Literatur
1.
Alden, K., Read, M., Andrews, P.S., Timmis, J., Coles, M.: Applying spartan to understand parameter uncertainty in simulations. R J. 6(2), 1–18 (2014)
2.
Barca, J.C., Sekercioglu, Y.A.: Swarm robotics reviewed. Robot. 31, 1–15 (2012)
3.
Brutschy, A., Pini, G., Pinciroli, C., Birattari, M., Dorigo, M.: Self-organized task allocation to sequentially interdependent tasks in swarm robotics. Auton. Agents Multi-Agent Syst. 28, 101–125 (2014)CrossRef
4.
Carlson, J., Murphy, R.R.: How UGVs physically fail in the field. IEEE Trans. Robot. 21(3), 423–437 (2005)CrossRef
5.
Christensen, A.L., Grady, R.O., Dorigo, M.: From fireflies to fault-tolerant swarms of robots. IEEE Trans. Evol. Comput. 13(4), 754–766 (2009)CrossRef
6.
Dorigo, M., Floreano, D., Gambardella, L.M., et al.: Swarmanoid: a novel concept for the study of heterogeneous robotic swarms. IRIDIA, Brussels, Belgium, Technical report 11–14 July (2011)
7.
Ferrante, E., Turgut, A.E., Dué, E., Dorigo, M.: Evolution of self-organized task specialization in robot swarms. PLoS Comput. Biol. 11, 1–21 (2015)CrossRef
8.
Goldberg, D., Matarie, M.J.: Design and evaluation of robust behavior-based controllers for distributed multi-robot collection tasks. In: Robot Teams: From Diversity to Polymorphism, pp. 1–24 (2001)
9.
Hart, A.G., Ratnieks, F.L.W.: Task partitioning, division of labour and nest compartmentalisation collectively isolate hazardous waste in the leafcutting ant atta cephalotes. Behav. Ecol. Sociobiol. 49(5), 387–392 (2001)CrossRef
10.
Humza, R., Scholz, O., Mokhtar, M., Timmis, J., Tyrrell, A.: Towards energy homeostasis in an autonomous self-reconfigurable modular robotic organism. In: Computation World: Future Computing, Service Computation, Adaptive, Content, Cognitive, Patterns, Computation World 2009, pp. 21–26 (2009)
11.
Johnson, B.R.: Task partitioning in honey bees: the roles of signals and cues in group-level coordination of action. Behav. Ecol. 21(6), 1373–1379 (2010)CrossRef
12.
Li, X., Parker, L.E.: Sensor analysis for fault detection in tightly-coupled multi-robot team tasks. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3269–3276, April 2007
13.
Long, M., Murphy, R., Parker, L.: Distributed multi-agent diagnosis and recovery from sensor failures. In: Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), vol. 3, pp. 2506–2513, October 2003
14.
Parker, L.E.: ALLIANCE: an architecture for fault tolerant multirobot cooperation. IEEE Trans. Robot. Autom. 14(2), 220–240 (1998)CrossRef
15.
Parker, L.E., Kannan, B.: Adaptive causal models for fault diagnosis and recovery in multi-robot teams. In: IEEE International Conference on Intelligent Robots and Systems, pp. 2703–2710 (2006)
16.
Pinciroli, C., Trianni, V., O’Grady et al.: ARGoS: a modular, multi-engine simulator for heterogeneous swarm robotics. In: IEEE International Conference on Intelligent Robots and Systems, pp. 5027–5034 (2011)
17.
Pini, G., Brutschy, A., Birattari, M., Dorigo, M.: Task partitioning in swarms of robots: reducing performance losses due to interference at shared resources. In: Cetto, J.A., Filipe, J., Ferrier, J.-L. (eds.) Informatics in Control Automation and Robotics. LNEE, vol. 85, pp. 217–228. Springer, Heidelberg (2011)CrossRef
18.
Pini, G., Brutschy, A., Scheidler, A., et al.: Task partitioning in a robot swarm: object retrieval as sequence of subtasks with direct object transfer. Artif. Life 20(3), 291–317 (2014)CrossRef
19.
Sahin, E.: Swarm robotics: from sources of inspiration. In: Swarm Robotics Workshop: State-of-the-Art Survey, pp. 10–20 (2005)
20.
Schmickl, T., Karsai, I.: Sting, carry and stock: how corpse availability can regulate de-centralized task allocation in a ponerine ant colony. PloS one 9(12), e114611 (2014)CrossRef
21.
Tarapore, D., Lima, P.U., Carneiro, J., Christensen, A.L.: To err is robotic, to tolerate immunological: fault detection in multirobot systems. Bioinspir. Biomim. 10(1), 016014 (2015)CrossRef
22.
Timmis, J., Tyrrell, A., Mokhtar, M., Ismail, A., Owens, N., Bi, R.: An artificial immune system for robot organisms. In: Symbiotic Multi-Robot Organisms: Reliability, Adaptability, pp. 279–302 (2010)
23.
Winfield, A.F.T., Harper, C.J., Nembrini, J.: Towards dependable swarms and a new discipline of swarm engineering. In: Şahin, E., Spears, W.M. (eds.) Swarm Robotics 2004. LNCS, vol. 3342, pp. 126–142. Springer, Heidelberg (2005)CrossRef
Metadaten
Titel
Dynamic Task Partitioning for Foraging Robot Swarms
verfasst von
Edgar Buchanan
Andrew Pomfret
Jon Timmis
Copyright-Jahr
2016
Buch
Swarm Intelligence

Print ISBN: 978-3-319-44426-0

Electronic ISBN: 978-3-319-44427-7

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-44427-7_10