Abstract
Modular robots are automated modules that can change their morphology self-sufficiently and progressively for control or reconfiguration purposes. Self-reconfiguration is a very challenging problem in modular robots systems. Existing algorithms are complex and not suitable for low resources devices. In this paper, we propose a parallel and fully distributed cluster-based algorithm to convert a set of blocks/modules in a new geometrical configuration. We proposed a cluster based self-reconfiguration algorithm. The main idea is to study the impact of clustering on the self-reconfiguration problem. The modules in each cluster remain together and try to move in order to find the final configuration. Based on this concept, our algorithm operates in parallel in each cluster to fasten reconfiguration process and ultimately the set of blocks will reach the desirable shape. We evaluate our algorithm on the centimeter-scale sliding blocks, developed in the Smart Blocks project in a simulator showing the entire reconfiguration process in real-time. We show the effectiveness of our algorithm, especially the benefits of clustering in self-reconfiguration task by comparing performance of both approaches (with and without clustering) while varying the number of clusters.
This work has been supported by the EIPHI Graduate School (contract ANR-17-EURE-0002).
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Moussa, M., Piranda, B., Makhoul, A., Bourgeois, J. (2021). Cluster-Based Distributed Self-reconfiguration Algorithm for Modular Robots. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 225. Springer, Cham. https://doi.org/10.1007/978-3-030-75100-5_29
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