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Swarms of self-assembling artefacts

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Self-assembling robots

Swarm intelligence is one of the most interesting research fields that studies the capabilities of self-organising and self-assembling as shown by social insects and other animal societies. Inspired by such studies, robotics exploited some of their principles in engineering, aiming at constructing an artefact with such capabilities.

Industrial Technologies

Such an artefact called swarm-bot system is composed of a number of simpler, insect-like robots, the s-bots. The activity where more than one s-bots physically connect to each other to form a swarm-bot constitutes one of the most distinguishing characteristics of the swarm-bot system, the autonomous self-assembling. The key idea behind this relies on the fact that difficult situations can not cannot be addressed by a single s-bot requiring the cooperative effort performed by the swarm-bot system. Therefore, self-assembling can improve the efficiency of an aggregation of autonomous cooperating s-bots under various complex environmental conditions. For instance, self-assembling reduces the risk of toppling over when moving in a particularly rough terrain. Self-assembling could also be useful for bridging a gap between the two sides of a trough that is larger in size than an s-bot, minimising the possibilities of falling in it. A swarm-bot system could also push/pull a massive or heavy object more easily than a single s-bot. Self-assembling is initiated with an s-bot turning its red lights on, attracting s-bots being in within its proximity by perceiving the red lights. The s-bots approach the red-lit s-bot and connect to it by grasping the red s-bot ring with their gripper. After a successful connection, they turn on their lights to attract other s-bots. In case of difficulties in approaching, there is a backward movement followed by a new attempt to re-approach. The developed self-assembling controllers have been based on a perceptron-type neural network whose weights evolved using an evolutionary algorithm. Synthesis of these controllers was performed during simulation of up to five simulated s-bots and then ported to the real s-bots. Experimental results showed that the procedure is reliable in controlling the connection of s-bots to each other or to special luminous objects (s-toys). Additionally, the procedure features scalability as up to 16 s-bots have successfully undergone experimental tests. Most importantly, it is a robust procedure exerting control to self-assembling s-bots moving on both flat and moderately rough terrain.

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