Abstract
Evolutionary robotics applies the selection, variation, and heredity principles of natural evolution to the design of robots with embodied intelligence. It can be considered as a subfield of robotics that aims to create more robust and adaptive robots. A pivotal feature of the evolutionary approach is that it considers the whole robot at once, and enables the exploitation of robot features in a holistic manner. Evolutionary robotics can also be seen as an innovative approach to the study of evolution based on a new kind of experimentalism. The use of robots as a substrate can help address questions that are difficult, if not impossible, to investigate through computer simulations or biological studies. In this paper we consider the main achievements of evolutionary robotics, focusing particularly on its contributions to both engineering and biology. We briefly elaborate on methodological issues, review some of the most interesting findings, and discuss important open issues and promising avenues for future work.
Highlights
In designing a robot, many different aspects must be considered simultaneously: its morphology, sensory apparatus, motor system, control architecture, etc. (Siciliano and Khatib, 2008)
EVOLUTIONARY ROBOTICS: FOR WHOM? we look at the research communities, which stand to benefit most immediately from Evolutionary robotics (ER)
Another way of classifying the contributions of evolutionary robotics to biology is in terms of whether they seek to extend abstract models through embodiment, or to carefully simulate existing features observed from real data in order to better understand how and why they evolved (Long, 2012)
Summary
Many different aspects must be considered simultaneously: its morphology, sensory apparatus, motor system, control architecture, etc. (Siciliano and Khatib, 2008). The sensory apparatus, morphology, and control of the robot are closely interdependent, and any change in a given part is likely to have a large influence on the functioning of the others Considering all these aspects at the same time contrasts with the straightforward approach in which they are all studied in isolation. The concept of embodied intelligence (Pfeifer and Bongard, 2007) is an alternative point of view in which the robot, its environment, and all the interactions between its components are studied as a whole Such an approach makes it possible to design systems with a balance of complexity between their different parts, and it generally results in simpler and better systems. The expected results of ER for a broad scientific and engineering community
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