Abstract
Cooperative object transport in distributed multi-robot systems requires the coordination and synchronisation of pushing/pulling forces by a group of autonomous robots in order to transport items that cannot be transported by a single agent. The results of this study show that fairly robust and scalable collective transport strategies can be generated by robots equipped with a relatively simple sensory apparatus (i.e. no force sensors and no devices for direct communication). In the experiments described in this paper, homogeneous groups of physical e-puck robots are required to coordinate and synchronise their actions in order to transport a heavy rectangular cuboid object as far as possible from its starting position to an arbitrary direction. The robots are controlled by dynamic neural networks synthesised using evolutionary computation techniques. The best evolved controller demonstrates an effective group transport strategy that is robust to variability in the physical characteristics of the object (i.e. object mass and size of the longest object’s side) and scalable to different group sizes. To run these experiments, we designed, built, and mounted on the robots a new sensor that returns the agents’ displacement on a 2D plane. The study shows that the feedback generated by the robots’ sensors relative to the object’s movement is sufficient to allow the robots to coordinate their efforts and to sustain the transports for an extended period of time. By extensively analysing successful behavioural strategies, we illustrate the nature of the operational mechanisms underpinning the coordination and synchronisation of actions during group transport.
Similar content being viewed by others
Notes
Data and graphs not shown in the papers, as well as movies of physical and simulated robots can be found at http://www.aber.ac.uk/en/cs/research/ir/dss/#swarm-robotics.
References
Aiyama, Y., Hara, M., Yabuki, T., Ota, J., & Arai, T. (1999). Cooperative transportation by two four-legged robots with implicit communication. Robotics and Autonomous Systems, 29(1), 13–19.
Alkilabi, M. H. M., Lu, C., & Tuci, E. (2015). Cooperative object transport using evolutionary swarm robotics methods. In P. Andrews, L. Caves, R. Doursat, S. Hickinbotham, F. Polack, S. Stepney, T. Taylor, & J. Timmis (Eds.), Proceedings of the European conference on artificial life (Vol. 1, pp. 464–471). Cambridge: MIT.
Alkilabi, M. H. M., Narayan, A., Lu, C., & Tuci, E. (2016a). Evolving group transport strategies for e-puck robots: moving objects towards a target area. In R. Groß, et al. (Eds.), Proceedings of the international symposium on distributed autonomous robotic systems (DARS). Berlin: Springer STAR.
Alkilabi, M. H. M., Narayan, A., & Tuci, E. (2016b). Design and analysis of proximate mechanisms for cooperative transport in real robots. In M. Dorigo, M. Birattari, X. Li, M. Lpez-Ibez, K. Ohkura, C. Pinciroli, et al. (Eds.), Proceedings of the 10th international conference on swarm intelligence (ANTS) (pp. 101–112). Berlin: Springer.
Bayındır, L. (2016). A review of swarm robotics tasks. Neurocomputing, 172, 292–321.
Beer, R. D., & Gallagher, J. C. (1992). Evolving dynamic neural networks for adaptive behavior. Adaptive Behavior, 1(1), 91–122.
Berman, S., Lindsey, Q., Sakar, M. S., Kumar, V., & Pratt, S. C. (2011). Experimental study and modeling of group retrieval in ants as an approach to collective transport in swarm robotic systems. Proceedings of the IEEE, 99(9), 1470–1481.
Birattari, M., Delhaisse, B., Francesca, G., & Kerdoncuff, Y. (2016). Observing the effects of overdesign in the automatic design of control software for robot swarms. In M. Dorigo, M. Birattari, X. Li, M. Lpez-Ibez, K. Ohkura, C. Pinciroli, et al. (Eds), Proceedings of the 10th international conference on swarm intelligence (ANTS) (pp. 149–160). Berlin: Springer.
Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: From natural to artificial systems. Oxford: Oxford University Press.
Brambilla, M., Ferrante, E., Birattari, M., & Dorigo, M. (2013). Swarm robotics: A review from the swarm engineering perspective. Swarm Intelligence, 7(2), 1–41.
Chen, J., Gauci, M., Li, W., Kolling, A., & Gross, R. (2015). Occlusion-based cooperative transport with a swarm of miniature mobile robots. IEEE Transactions on Robotics, 31(2), 307–321.
Conover, W. J. (1999). Practical nonparametric statistics. New York: Wiley.
Czaczkes, T. J., Nouvellet, P., & Ratnieks, F. (2011). Cooperative food transport in the neotropical ant pheidole oxyops. Insectes Sociaux, 58(2), 153–161.
Czaczkes, T. J., & Ratnieks, F. (2013). Cooperative transport in ants (hymenoptera: Formicidae) and elsewhere. Myrmecological News, 18, 1–11.
Dorigo, M., & Şahin, E. (2004). Guest editorial. Special Issue: Swarm Robotics Automatic Robotics, 17(2–3), 111–113.
Feener, J. R., Donald, H., & Moss, K. A. G. (1990). Defense against parasites by hitchhikers in leaf-cutting ants: A quantitative assessment. Behavioral Ecology and Sociobiology, 26(1), 17–29.
Francesca, G., Brambilla, M., Brutschy, A., Garattoni, L., Miletitch, R., Podevijn, G., et al. (2015). AutoMoDe-Chocolate: Automatic design of control software for robot swarms. Swarm Intelligence, 9(2–3), 125–152.
Gelblum, A., Pinkoviezky, I., Fonio, E., Ghosh, A., Gov, N., & Feinerman, O. (2015). Ant groups optimally amplify the effect of transiently informed individuals. Nature Communications, 6, 1–9. doi:10.1038/ncomms8729.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. Reading, MA: Addison-Wesley.
Groß, R., & Dorigo, M. (2004a). Cooperative transport of objects of different shapes and sizes. In M. Dorigo, M. Birattari, C. Blum, L. M. Gambardella, F. Mondada, & T. Stützle, (Eds.), Proceedings of the 4th international workshop on ant colony optimization and swarm intelligence, volume 3172 of LNCS (pp. 106–117). Berlin: Springer.
Groß, R., & Dorigo, M. (2004b). Group transport of an object to a target that only some group members may sense. In X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervs, J. A. Bullinaria, et al. (Eds). Proceedings of the 8th international conference on parallel problem solving from nature (PPSN) (pp. 852–861). Berlin: Springer.
Groß, R., & Dorigo, M. (2008). Evolution of solitary and group transport behaviors for autonomous robots capable of self-assembling. Adaptive Behavior, 16(5), 285–305.
Groß, R., & Dorigo, M. (2009). Towards group transport by swarms of robots. International Journal of Bio-Inspired Computation, 1(1), 1–13.
Groß, R., Mondada, F., & Dorigo, M. (2006a). Transport of an object by six pre-attached robots interacting via physical links. In Proceedings of the IEEE international conference on robotics and automation (ICRA) (pp. 1317–1323). IEEE.
Groß, R., Tuci, E., Dorigo, M., Bonani, M., & Mondada, F. (2006b). Object transport by modular robots that self-assemble. In Proceedings of the IEEE international conference on robotics and automation (ICRA) (pp. 2558–2564). IEEE.
Habibi, G., Kingston, Z., Xie, W., Jellins, M., & McLurkin, J. (2015). Distributed centroid estimation and motion controllers for collective transport by multi-robot systems. In A. Okamura et. al. (Eds.), Proceedings of the IEEE international conference on robotics and automation (ICRA) (pp. 1282–1288). IEEE.
Habibi, G., Xie, W., Jellins, M., & McLurkin, J. (2014). Distributed path planning for collective transport using homogeneous multi-robot systems. In M. Ani Hsieh, & G. Chirikjian, (Eds). Proceedings of the 12th international symposium on distributed autonomous robotic systems (DARS) (pp. 151–164). Berlin: Springer.
Hölldobler, B., Stanton, R., & Markl, H. (1978). Recruitment and food-retrieving behavior in novomessor (formicidae, hymenoptera). Behavioral Ecology and Sociobiology, 4(2), 163–181.
Huntsberger, T., Rodriguez, G., & Schenker, P. (2000). Robotics challenges for robotic and human mars exploration. In W. Stone (Ed.), Proceedings of the robotics 2000. ASCE. doi:10.1061/9780784404768.
Kube, C. R., & Bonabeau, E. (2000). Cooperative transport by ants and robots. Robotics and Autonomous Systems, 30, 85–101.
Kube, C. R., & Zhang, H. (1997). Task modelling in collective robotics. In R. C. Arkin & G. A. Bekey (Eds.), Robot colonies (pp. 53–72). Berlin: Springer.
McCreery, H. F., & Breed, M. D. (2014). Cooperative transport in ants: A review of proximate mechanisms. Insects Sociaux, 61, 99–110.
McCreery, H. F., Dix, Z. A., Breed, M. D., & Nagpal, R. (2016). Collective strategy for obstacle navigation during cooperative transport by ants. bioRxiv. http://biorxiv.org/content/biorxiv/early/2016/06/29/061036.full.
Moffett, M. W. (1992). Ant foraging. Research and Exploration, 8, 220–231.
Mondada, F., Bonani, M., Raemy, X., Pugh, J., Cianci, C., Klaptocz, A., et al. (2009). The e-puck, a robot designed for education in engineering. In Proceeding of the 9th international conference on autonomous robot systems and competitions (vol. 1, pp. 59–65). IEEE.
Nouyan, S., Groß, R., Dorigo, M., Bonani, M., & Mondada F. (2006). Group transport along a robot chain in a self-organised robot colony. In T. Arai et. al., (Eds). Proceedings of the 9th international conference on intelligent autonomous systems (pp. 433–442). IOS Press.
Parker, C., & Zhang, H. (2006). Collective robotic site preparation. Adaptive Behavior, 14(1), 5–19.
Pettinaro, G., Gambardella, L.-M., & Ramirez-Serrano, A. (2005). Adaptive distributed fetching and retrieval of goods by a swarm-bot. In B. Hannaford, G. Bekey, P. Fiorini, Y. Nakamura, L. Bushnell, D. Fox, et al., (Eds.), Proceedings of the 12th international conference on advanced robotics (ICAR) (pp. 825–832). IEEE.
Robson, S. K., & Traniello, J. (1998). Resource assessment, recruitment behavior, and organization of cooperative prey retrieval in the ant Formica schaufussi (hymenoptera: Formicidae). Insect Behavior, 11, 1–22.
Tanner, C. J. (2008). Resource characteristics and competition affect colony and individual foraging strategies of the wood ant formica integroides. Ecological Entomology, 33(1), 127–136.
Trianni, V., Tuci, E., Ampatzis, C., & Dorigo, M. (2014). Evolutionary swarm robotics: A theoretical and methodological itinerary from individual neuro-controllers to collective behaviours. In P. A. Vargas, E. Di Paolo, I. Harvey, & P. Husbands (Eds.), The horizons of evolutionary robotics (pp. 153–178). Cambridge, MA: MIT Press.
Wang, Y., & de Silva, C. W. (2006). Cooperative transportation by multiple robots with machine learning. In G. Yen, et al. (Eds.), Proceedings of the IEEE congress on evolutionary computation (CEC) (pp. 3050–3056). IEEE.
Wang, Z., & Schwager, M. (2015). Multi-robot manipulation with no communication using only local measurements. In Y. Ohta et al. (Eds.), Proceeding of the 54th IEEE conference on decision and control (CDC) (pp. 380–385). IEEE.
Wang, Z., & Schwager, M. (2016). Kinematic multi-robot manipulation with no communication using force feedback. In D. Kragic et al., (Eds.), Proceedings of the IEEE international conference on robotics and automation (ICRA) (pp. 427–432). IEEE.
Wang, Z., Takano, Y., Hirata, Y., & Kosuge, K. (2004). A pushing leader based decentralized control method for cooperative object transportation. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (vol. 1, pp. 1035–1040). IEEE.
Woern, H., Szymanski, M., & Seyfried, J. (2006). The i-swarm project. In K. Dautenhahn et al. (Eds.), Proceeding of the 15th IEEE international symposium on robot and human interactive communication (pp. 492–496). IEEE.
Yamamoto, A., Ishihara, S., & Fuminori, I. (2009). Fragmentation or transportation: Mode of large-prey retrieval in arboreal and ground nesting ants. Insect Behavior, 22, 1–11.
Acknowledgements
Muhanad H. Mohammed Alkilabi thanks Iraqi Ministry of Higher Education and Scientific Research for funding his PhD. The authors would like to thank G. Francesca and M. Birattari for their support with the statistical analysis of the physical robots performances.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Alkilabi, M.H.M., Narayan, A. & Tuci, E. Cooperative object transport with a swarm of e-puck robots: robustness and scalability of evolved collective strategies. Swarm Intell 11, 185–209 (2017). https://doi.org/10.1007/s11721-017-0135-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11721-017-0135-8