Title
Soft-bodied amoeba-inspired robot that switches between qualitatively different behaviors with decentralized stiffness control
Abstract
The goal of this research is to understand the underlying mechanism of the behavioral diversity of animals and then use the findings to build truly adaptive robots. Behavioral diversity is an inherent feature of all animals, and it is also important for robots to perform adaptively in unknown and dynamically changing environments. This feature enables animals to select adaptive behavior from among versatile behaviors. However, most designers have avoided or ignored behavioral diversity while constructing artificial systems, with the aim of achieving highly optimized performance in specific environments for given tasks; this leads to vulnerability of these systems to environmental changes. To understand how behavioral diversity can be embedded into artificial systems, we focus on a large amoeba-like unicellular organism, i.e., the plasmodium of true slime mold Physarum polycephalum, in this study. Despite the absence of a central nervous system, the plasmodium exhibits various types of locomotion i.e., exploratory, taxis, and escape behaviors and switches its behavior depending on the environment. Inspired by this primitive yet intelligent living organism, we build a modular robot that exhibits exploratory and taxis locomotions, and spontaneously switches between them in a fully decentralized manner according to the situation encountered. The results are expected to shed new light on a design scheme for life-like robots that exhibit amazingly versatile and adaptive behaviors.
Year
DOI
Venue
2015
10.1177/1059712314564784
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Keywords
Field
DocType
Behavioral diversity,decentralized control,biologically inspired robot,soft-bodied robot
Decentralised system,Unicellular organism,Computer science,Taxis,Artificial intelligence,Modular design,Robot,Adaptive behavior,Organism,Physarum polycephalum
Journal
Volume
Issue
ISSN
23
2
1059-7123
Citations 
PageRank 
References 
3
0.42
5
Authors
3
Name
Order
Citations
PageRank
Takuya Umedachi17615.88
Kentaro Ito251.21
Akio Ishiguro332160.94