Evolutionary Modular Robotics: Survey and Analysis
Loading...
Authors
Alattas, Reem
Patel, Sarosh
Sobh, Tarek M.
Issue Date
2018-07-16
Type
Article
Language
en_US
Keywords
Evolutionary robotics , Modular robots , Task-based design , Self-assembly , Self-reconfiguration , Self-repair , Self-reproduction
Alternative Title
Abstract
This paper surveys various applications of artificial evolution in the field of modular robots. Evolutionary robotics aims to design autonomous adaptive robots automatically that can evolve to accomplish a specific task while adapting to environmental changes. A number of studies have demonstrated the feasibility of evolutionary algorithms for generating robotic control and morphology. However, a huge challenge faced was how to manufacture these robots. Therefore, modular robots were employed to simplify robotic evolution and their implementation in real hardware. Consequently, more research work has emerged on using evolutionary computation to design modular robots rather than using traditional hand design approaches in order to avoid cognition bias. These techniques have the potential of developing adaptive robots that can achieve tasks not fully understood by human designers. Furthermore, evolutionary algorithms were studied to generate global modular robotic behaviors including; self-assembly, self-reconfiguration, self-repair, and self-reproduction. These characteristics allow modular robots to explore unstructured and hazardous environments. In order to accomplish the aforementioned evolutionary modular robotic promises, this paper reviews current research on evolutionary robotics and modular robots. The motivation behind this work is to identify the most promising methods that can lead to developing autonomous adaptive robotic systems that require the minimum task related knowledge on the designer side.
Description
Citation
Alattas, R.J., Patel, S. & Sobh, T.M. Evolutionary Modular Robotics: Survey and Analysis. J Intell Robot Syst 95, 815–828 (2019). https://doi-org.libproxy.bridgeport.edu/10.1007/s10846-018-0902-9
Publisher
Springer