Photomorphogenesis for robot self-assembly: adaptivity, collective decision-making, and self-repair.

摘要: Self-assembly in biology is an inspiration for engineered large-scale multi-modular systems with desirable characteristics, such as robustness, scalability, and adaptivity. Previous works have shown that simple mobile robots can be used to emulate study self-assembly behaviors. However, many of these studies were restricted rather static inflexible aggregations predefined shapes, limited adaptivity compared observed nature. We propose a photomorphogenesis approach using our vascular morphogenesis model-a light-stimuli directed method multi-robot inspired by the tissue growth trees. Robots role 'leaves' collect virtual resource proportional real, sensed environmental feature. This then build underlying network shares common throughout whole robot aggregate determines where it grows or shrinks reaction dynamic environment. In use supplemental bioinspired models collectively select leading decide who starts self-assemble (and where), assemble aggregations. The model way preferring bright areas, hence resembling natural phototropism (growth towards light). Our main result assembled are adaptive able react environments autonomously rearranging aggregate, discarding outdated parts, growing new ones. representative experiments, self-assembling make rational decisions on grow. Cutting off parts triggers self-organizing repair process robots, regrow. All capabilities adaptivity, collective decision-making, self-repair originate directly from self-organized behavior model. opens up opportunities reconfiguration short time-scales high forms structures.