Object Transportation by Granular Convection Using Swarm Robots
We propose a novel method for object transport using granular convection, in which the granular material is a robot swarm consisting of small robots with minimal sensors. Granular convection is commonly observed in the “Brazil Nut Effect”. In this work, we consider the transported object to be passive, however, and not actuated like the surrounding granular material. We show that the passive object can be transported to a given destination in spite of the fact that each robot does not know the location of the object being transported nor the location of the destination. Each robot moves based solely on a weak repulsive force from the destination and stochastic perturbations. We first show fundamental characteristics of a system with no communication between robots. We observe that very high or very low robot densities are detrimental to object transport. We then show that heterogeneous swarms increase performance. We propose two types of heterogeneous swarm systems: a swarm in which robots switch states probabilistically, and a swarm in which state propagates using local communication. The signal propagation system shows the best performance in terms of success rate and accuracy in a wide range of densities.
KeywordsConvection Transportation Boulder Larg
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- 4.Fuchiwaki, O., Ito, A., Misaki, D., Aoyama, H.: Multi-axial micromanipulation organized by versatile micro robots and micro tweezers. In: IEEE Int. Conf. on Robotics and Automation, pp. 893–898 (2008)Google Scholar
- 6.Mataric, M.J., Nilsson, M., Simsarian, K.T.: Cooperative multi-robot box-pushing. In: Proc. of Int. Conf. on Intelligent Robots and Systems, pp. 556–561 (1995)Google Scholar
- 7.Kube, C.R., Zhang, H.: The use of perceptual cues in multi-robot box-pushing. In: Proc. of Int. Conf. on Robotics and Automation, pp. 2085–2090 (1996)Google Scholar
- 9.Spletzer, J., Das, A.K., Fierro, R., Taylor, C.J., Kumar, V., Ostrowski, J.P.: Cooperative localization and control for multi-robot manipulation. In: Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, pp. 631–636 (2001)Google Scholar
- 11.Takahashi, K., Ogawa, N., Oku, H., Hashimoto, K.: Organized Motion Control of a lot of Microorganisms Using Visual Feedback. In: Proc. of the IEEE Intl. Conf. on Robotics and Automation, pp. 1408–1413 (2006)Google Scholar
- 13.Groß, R., Magnenat, S., Mondada, F.: Segregation in swarms of mobile robots based on the brazil nut effect. In: Proc. of Int. Conf. on Intelligent Robots and Systems, pp. 4349–4356 (2009)Google Scholar
- 14.Chen, J., Gauci, M., Price, M.J., Groß, R.: Segregation in swarms of e-puck robots based on the brazil nut effect. In: Proc. of the 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2012), pp. 163–170. ACM Press (2012)Google Scholar
- 15.Williams, J., Khan, M.: The mixing and segregation of particulate solids of different particle size. Chem. Eng. 269, 19–25 (1973)Google Scholar
- 19.Dhariwal, A., Sukhatme, G., Requicha, A.: Bacterium-inspired robots for environmental monitoring. In: Proc. of the IEEE Intl. Conf. on Robotics and Automation, pp. 1436–1443 (2004)Google Scholar