The body of robots and their controllers need to be adapted to the task that they carry out. While it is possible to design and optimize free-form morphologies, its physical implementation consumes too many resources. In contrast, modular robots provide a feasible approach to design robotic morphologies that can be deployed in minutes, making them a suitable tool to implement virtual creatures. In this article, we tackle the main challenges to consider when evolving modular robots and mention some opportunities that these systems can provide.

We describe experimentation with robots together with computer vision to improve various artificial chemical life systems. We investigate a case study, where the use of the robot enables timely, and precise verification of the experiment results with fixed parameters. In addition, new possibilities to promote the quality of artificial life experiments, such as positioning droplets at equidistant intervals or in patterns are discussed.

Liquid handling robots are rarely used in the domain of artificial life. In this field, transitory behaviours of non-equilibrium man-made systems are studied and need an automatic monitoring and logging of results. In addition, artificial life experiments are dynamic with frequent changes, which makes it difficult to apply conventional liquid handling robots as they are designed to automate a pre-defined task. In order to address these issues, we have developed an open source liquid handling robot, EvoBot. It uses a modular approach, which gives us the possibility to reconfigure the robot for different experiments and make it possible for users to add functionality by just developing a function specific module. In addition, it provides sensors and extra functionality for monitoring an experiment, which allows researchers to perform interactive experiments with the aim of prolonging non- equilibrium conditions. In this paper, we describe the modular design of EvoBot, document its performance, and provide a novel example of an interactive experiment in artificial life, where the robot nurtures a microbial fuel cell based on its voltage output.

Due to the replacement of natural flora and fauna with urban environments, a significant part of the earths organisms that function as primary consumers have been dispelled. To compensate for the reduction in the amount of primary consumers, robotic systems that mimic plant-like organisms are interesting to mimic for their potential functional and aesthetic value in urban environments. To investigate how to utilize plant developmental strategies in order to engender urban artificial plants, we built a simple evolutionary model that applies an L-System based grammar as an abstraction of plant development. In the presented experiments, phytomorphologies (plant morphologies) are iteratively constructed using a context sensitive L-System. The genomic representation of the L-System is subject to mutation by an evolutionary algorithm. These mutations thus alter the developmental rules of these phytomorphologies. We compare the differences between the light absorption of evolving virtual plants that remain static during their life and virtual plants that possess the possibility to move joints that link the separate parts of the virtual plants. Our results show that our evolutionary algorithm did not exploit potential beneficial joint actuation, instead, mostly static structures evolved. The results of our evolving L-System show that it is able to create various phytomorphologies, albeit that the results are preliminary and will be more thoroughly investigated in the future.