Entropy | |
Guided Self-Organization in a Dynamic Embodied System Based on Attractor Selection Mechanism | |
Surya G. Nurzaman1  Yongjae Kim1  Xiaoxiang Yu1  Fumiya Iida1  | |
[1] Bio-Inspired Robotics Laboratory, Department of Mechanical and Process Engineering, ETH Zürich, Zürich, Switzerland; | |
关键词: guided self-organization; embodied system; attractor selection mechanism; mechanical dynamics; stochastic perturbation; sensory input; goal directed locomotion; curved beam hopping robot; | |
DOI : 10.3390/e16052592 | |
来源: DOAJ |
【 摘 要 】
Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics.
【 授权许可】
Unknown