期刊
EVOLUTIONARY COMPUTATION
卷 24, 期 2, 页码 205-236出版社
MIT PRESS
DOI: 10.1162/EVCO_a_00172
关键词
Evolutionary robotics; autonomous robots; controller synthesis; reality gap; online evolution; bootstrap problem; deception; genomic encoding; research practices
资金
- Fundacao para a Ciencia e a Tecnologia (FCT) [SFRH/BD/76438/2011, SFRH/BD/89573/2012, UID/EEA/50008/2013, UID/Multi/04046/2013, EXPL/EEI-AUT/0329/2013]
- Fundação para a Ciência e a Tecnologia [UID/Multi/04046/2013, SFRH/BD/89573/2012, EXPL/EEI-AUT/0329/2013, SFRH/BD/76438/2011] Funding Source: FCT
One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versusevolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1)the bootstrap problem, (2)deception, and (3)the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.
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