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Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, indefinite richness, and limited availability of information. Industrial robots, in contrast, operate in highly controlled environments with no or very little uncertainty. Although many challenges remain, concepts from biologically inspired (bio-inspired) robotics will eventually enable researchers to engineer machines for the real world that possess at least some of the desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility. [ABSTRACT FROM AUTHOR]

The decay in structure size of manufacturing products has yielded new demands on spontaneous composition methods. The key for the realization of small-sized robots lies in how to achieve the efficient assembly sequence in a bottom-up manner, where most of the parts have only limited (or no) computational (i.e. deliberative) abilities. In this paper, based on a novel self-assembly platform consisting of self-propulsive centimetre-sized modules capable of aggregation on the surface of water, we study the effect of stochasticity and morphology (shape) on the yield of targeted formations in self-assembly processes. Specifically, we focus on a unique phenomenon: that a number of modules instantly compose a target product without forming intermediate subassemblies, some of which constitute undesired geometrical formations (termed one-shot aggregation). Together with a focus on the role that the morphology of the modules plays, we validate the effect of one-shot aggregation with a kinetic rate mathematical model. Moreover, we examined the degree of parallelism of the assembly process, which is an essential factor in self-assembly, but is not systematically taken into account by existing frameworks. [ABSTRACT FROM AUTHOR]

Self-organization is a phenomenon found in biomolecular self-assembly by which proteins are spontaneously driven to assemble and attain various functionalities. This study reports on self-organized behavior in which distributed centimeter-sized modules stochastically aggregate and exhibit a translational wheeling motion. The system consists of two types of centimeter-sized water-floating modules: a triangular-shaped module that is equipped with a vibration motor and a permanent magnet (termed the active module), which can quasi- randomly rove around; and circular modules that are equipped with permanent magnets (termed passive modules). In its quasi-random movement in water, the active module picks up passive modules through magnetic attraction. The contacts between the modules induce a torque transfer from the active module to the passive modules. This results in rotational motion of the passive modules. As a consequence of the shape difference between the triangular module and the circular module, the passive modules rotate like wheels, being kept on the same edges as the active module. The motion of the active module is examined, as well as the characteristics and behavior of the self-organization process. [ABSTRACT FROM AUTHOR]

Self-assembly is a key phenomenon whereby vast numbers of individual components passively interact and form organized structures, as can be seen, for example, in the morphogenesis of a virus. Generally speaking, the process can be viewed as a spatial placement of attractive and repulsive components. In this paper, we report on an investigation of how morphology, i.e., the shape of components, affects a self-assembly process. The experiments were conducted with 3 differently shaped floating tiles equipped with magnets in an agitated water tank. We propose a novel measure involving clustering coefficients, which qualifies the degree of parallelism of the assembly process. The results showed that the assembly processes were affected by the aggregation sequence in their early stages, where shape induces different behaviors and thus results in variations in aggregation speeds. [ABSTRACT FROM AUTHOR]