Evolutionary robotics is heading towards fully embodied evolution in real-time and real-space. In this paper we introduce the Triangle of Life, a generic conceptual framework for such systems in which robots can actually reproduce. This framework can be instantiated with different hardware approaches and different reproduction mechanisms, but in all cases the system revolves around the conception of a new robot organism. The other components of the Triangle capture the principal stages of such a system; the Triangle as a whole serves as a guide for realizing this anticipated breakthrough and building systems where robot morphologies and controllers can evolve in real-time and real-space. After discussing this framework and the corresponding vision, we present a case study using the SYMBRION research project that realized some fragments of such a system in modular robot hardware.

SUMMARY Imperfect synchrony between male calls occurs in the acoustically interacting bushcricket Mecopoda elongata, and males establishing the temporal leadership attract more females in choice experiments. An asymmetrical representation of leader and follower signals in pairs of direction-selective neurons of the auditory pathway was suggested to represent the neural basis for the preference of females. We investigated the time–intensity trading effect, which occurs when the temporal advantage of the leader signal is compensated, and can be reversed, by an additional sound pressure level of the follower. In behavioural arena trials the intensity trading of the preference of females for leader signals depends on the playback level; a higher sound pressure level (SPL) is needed for compensation at higher playback levels. We studied the simultaneous neuronal representation of leader and follower signals, and the time–intensity trading function in the pair of omega-neurons in the CNS. Consistent with the behavioural data, the representation of leader and follower signals can be reversed with an additional loudness of the follower, and the steepness of the trading function depends on the playback level. We also implemented data on the neuronal representation of synchronized signals in individual receivers into computer-based agents, which performed phonotaxis in a virtual sound field. Results of these simulations closely resemble those obtained from real females with respect to the overall preference under the various time–intensity trading conditions. Furthermore, in combination with the observed trading functions these simulations demonstrate, that under more realistic field conditions the ultimate success of followers in attracting females is much higher than suggested from arena trials. We discuss the evolutionary consequences for male calling strategies in synchronously calling Orthoptera.

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Abstract-One of the prominent challenges in mobile robotics is to develop control methodologies that allow the adaptation to dynamic and unforeseen environments. The classic approach of hand-coded controllers is very efficient for well-defined tasks and specific environments but poor in adapting to changing environmental conditions. One alternative approach is the application of evolutionary algorithms which need, in turn, easily evolvable representations of controllers. In this paper, we investigate one promising approach of an artificial hormone system as a control paradigm which is believed to be easily optimized by evolutionary processes. In a first step of this research, we focus on the simple task of collision avoidance. We present a brief mathematical analysis of this controller approach and an implementation of the controller on a mobile robot to check the feasibility in principle of our approach. The task is successfully accomplished and we conclude with a discussion of the hormone dynamics in the robot.

Abstract-Self-organization in natural systems demonstrates very reliable and scalable collective behavior without using any central elements. When providing collective robotic systems with self-organizing principles, we are facing new problems of making self-organization purposeful, self-adapting to changing environments and faster, in order to meet requirements from a technical perspective. This paper describes on-going work of creating such an artificial self-organization within artificial robot organisms, performed in the framework of several European projects.