Grand Challenges for Evolutionary Robotics

Abstract

Evolutionary Robotics is a field that “aims to apply evolutionary computation techniques to evolve the overall design or controllers, or both, for real and simulated autonomous robots” (Vargas et al., 2014). This approach is “useful both for investigating the design space of robotic applications and for testing scientific hypotheses of biological mechanisms and processes” (Floreano et al., 2008). However, as noted in Bongard (2013) “the use of metaheuristics (i.e., evolution) sets this subfield of robotics apart from the mainstream of robotics research,” which “aims to continuously generate better behavior for a given robot, while the long-term goal of Evolutionary Robotics is to create general, robot-generating algorithms.” One could say that Evolutionary Robotics is a test ground or experimental toolbox to study various issues arising on the road to intelligent and autonomous machines. The related issues include embodied cognition and intelligence, self-organization and collective behavior, the emergence of communication and cooperation, co-evolution, neuro-evolution, and many more with robots forming the substrate or medium for the experiments (Nolfi and Floreano, 2000; Wang et al., 2006; Floreano et al., 2008; Trianni, 2008; Doncieux et al., 2011; Bongard, 2013; Vargas et al., 2014). Given the fact that many Evolutionary Robotics investigations are performed in simulation, there is a big overlap with a subfield in Artificial Life research that is concerned with evolving virtual creatures and societies. However, I think it is safe to say that robotics can be distinguished because it ultimately aims at real physical robots (a.k.a. intelligent machines, animate artifacts, or artificial organisms) that exist and operate in the real world. Their bodies can be made of traditional mechatronic components, (self-) assembled from simple modular units, formed by some soft material, 3D printed plastics, some fancy new stuff invented by material scientists, or any combination of these,but in the end the robots must be physical entities. Therefore, Grand Challenges for Evolutionary Robotics must be tangible. Furthermore, Grand Challenges should be demonstrations of evolution, either a particular property of it, or the process of evolution as a whole. In the following, I propose three Grand Challenges, subject to discussion. This list is not meant to capture the ultimate goals for the field. Rather, it is meant to inspire the community to deliberate and collectively identify the bold dreams that can lead further developments. This paper will have achieved its main goal if the list of Grand Challenges is discussed and revised, leading to an adjusted version that has a broad support.