Programmable matter i.e. matter that can change its physical properties, more likely its shape according to an internal or an external action is a good example of a cybermatics component. As it links a cyberized shape to real matter, it is a straight example of cyber-physical conjugation. But, this interaction between virtual and real worlds needs two elements. The first one is to find a way to represent the cyberized object using programmable matter and the second is to be able to adapt the matter to the cyberized changes. This article presents the progresses made in these two topics within the Claytronics project.
Modular self-reconfigurable robots are composed of independent connected modules which can self-rearrange their connectivity using processing, communication and motion capabilities, in order to change the overall robot structure. In this paper, we consider rolling cylindrical modules arranged in a two-dimensional vertical hexagonal lattice. We propose a parallel, asynchronous and fully decentralized distributed algorithm to self-reconfigure robots from an initial configuration to a goal one. We evaluate our algorithm on the millimeter-scale cylindrical robots, developed in the Claytronics project, through simulation of large ensembles composed of up to ten thousand modules. We show the effectiveness of our algorithm and study its performance in terms of communications, movements and execution time. Our observations indicate that the number of communications, the number of movements and the execution time of our algorithm is highly predictable. Furthermore, we observe execution times that are linear in the size of the goal shape.
Many distributed algorithms require a specific role to be played by a leader, a single node in the system. The choice of this node often has a direct impact on the performance. In particular, selecting a central node as the leader can significantly improve algorithm efficiency. Classical distributed algorithms require global information about the connectivity network to elect a centroid node. Thus, they are not suitable for large-scale distributed embedded systems with scarce computation, memory and energy resources. We present E2ACE, an Effective and Efficient ApproximateCentroid Election algorithm that uses O(1) memory space per node, O(d) time and O(mn 2 ) messages of size O(1), where n is the number of nodes, m the number of connections and d the diameter of the system. We evaluate our algorithm on the Blinky Blocks system using simulations. Experimental results show that E2ACE scales well in terms of accuracy, execution time and number of messages. We show that E2ACE is more accurate than the only existing algorithm with similar complexity results.
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