Abstract | In this paper we describe the evolution of a discrete-time recurrent neural network to control a real mobile robot. In all our experiments the evolutionary procedure is carried out entirely on the physical robot without human intervention. We showthat the autonomous development of a set of behaviors for locating a battery charger and periodically returning to it can be achieved by lifting constraints in the design of the robot/environment interactions that were employed in a preliminary experiment. The emergent homing behavior is based on the autonomous development ofaninternal neural topographic map (which is not pre-designed) that allows the robot to choose the appropriate trajectory as function of location and remaining energy.

The paper describes the results of the evolutionary development of a real, neural-network driven mobile robot. The evolutionary approach tothe development of neural controllers for autonomous agents has been successfully used by many researchers, but most-if not all- studies have been carried out with computer simulations. Instead, in this research the whole evolutionary process takes places entirely on a real robot without human intervention. Although the experiments described here tackle a simple task of navigation and obstacle avoidance, we show a number of emergent phenomena that are characteristic of autonomous agents. The neural controllers of the evolved best individuals display a full exploitation of non-linear and recurrent connections that make them more e cient than analogous man-designed agents. In order to fully understand and describe the robot behavior, we have also employed quantitative ethological tools [13], and showed that the adaptation dynamics conform to predictions made for animals. 1

The interaction of an autonomous mobile robot with the real world critically depends on the robots morphology and on its environment. Building a model of these aspects is extremely complex, making simulation insufficient for accurate validation of control algorithms. If simulation environments are often very efficient, the tools for experimenting with real robots are often inadequate. The traditional programming languages and tools seldom provide enought support for realtime experiments, thus hindering the understanding of the control algorithms and making the experimentation complex and time-consuming. A miniature robot is presented: it has a cylindrical shape measuring 55 mm in diameter and 30 mm in height. Due to its small size, experiments can be performed quickly and cost-effectively in a small working area. Small peripherals can be designed and connected to the basic module and can take advantage of a versatile communication scheme. A serial-link is provided to run control algorithms on a workstation during debugging, thereby giving the user the opportunity of employing all available graphical tools. Once debugged, the algorithm can be downloaded to the robot and run on its own processor. Experimentation with groups of robots is hardly possible with commercially available hardware. The size and the price of the described robot open the way to cost-effective investigations into collective behaviour. This aspect of research drives the design of the robot described in this paper. Experiments with some twenty units are planned for the near future.

This chapter addresses embodied social interaction inlif6 like agents. Embodiment is discussedf rom both arti cial intelligence and psychology viewpoints. Di#erent degreesof embodiment in biological, virtual and robotic agents are discussed, given the example of a bottomup, behavior-oriented, dynamic control of virtual robots. A `dancing with strangers' experiment shows how the same principles can be applied to physical robot-human interaction. We then discuss the issue of sociality which di#ers in di#erent academic communities with respect to which roles are attributed to genes, memes, and the individual embodied agent.

Behavior-based approach has been successfully applied to design the control system of a robot. This paper presents our approach, based on evolutionary algorithms, to program behavior-based robots automatically. Instead of handcoding all the behavior controllers or evolving an entire control system for an overall task, we suggest our approach at the intermediate level: it includes evolving behavior primitives and behavior arbitrators for a mobile robot to achieve the specified tasks. To examine the developed approach, we evolve a control system for a moderate complicated box-pushing task as an example. We first evolved the controllers in simulation and then transferred them to the Khepera miniature robot. Experimental results show the promise of our approach and the evolved controllers are transferred to the real robot without loss of performance. I. Introduction The behavior-based design has become a main alternative to traditional robot design nowadays. A number of behavior-based rob...

This paper is meant as a basis for discussion towards a framework for cognitive architectures integrating remembering, rehearsal, language and empathy. It describes the programmatic background of our concrete work on intelligent autonomous agents. The goal is to motivate a common framework which should inspire research on `artificial cognition' for autonomous robots as well as investigations on cognition in humans or other animals. 1 Introduction Our professional background are biology and artificial intelligence and we are mainly interested in the construction of intelligent autonomous agents based on biological and psychological findings and models. This paper outlines our research framework which grew out of considerations on cognition for artifacts, although we are aware that the successful implementation of these ideas is still a future goal. Instead of reviewing intensively literature of cognitive science and escpecially of cognitive psychology we focus on some points which are ...

This paper describes a vehicle to perform a simple task using a decision control composed of a behavior hierarchy. First the model is presented. It is based on two fundamental components: the behavior module defining how each behavior element is implemented; and the blocker which is the basic component of the arbitration system, responsible for behavior selection. Behavior modules are composed of two submodules, one to produce actuator actions and other to produce priorities associated to actions. They also have three parameters whose values can be changed prior to execution, as a means of configuring a particular control architecture. Competition among behaviors is resolved by arbitration structures, each one consisting of a series of blockers working in a completely distributed way. The arbitration system can be automatically generated from the mere enumeration of the constituting behaviors. The development of the model in order to support behavior hierarchies is also presented as we...

# This paper describes a method for analyzing the behavior of an autonomous robot. The robot is viewed as a continuous# stochastic dynamical system. The analysis starts from an empirical phase portrait. In a #rst stage# elementary regularities are detected. These regularities# called transient attractors# combine properties of attractors with properties of partition cells of phase space. As the system trajectory passes through these regularities repeatedly# a sequence of identi#able events is produced# which can be interpreted as a symbol sequence. This sequence is further analyzed in the second stage# where a #nite description of temporal regularities within it is constructed. This description comes in the format of a variety of #nite#state automata. In a third stage# higher#order regularities in this #nite#state#like description are identi#ed. This yields a hierarchic behavior model. At all stages# regularities are de#ned using criteria of maximal local predictability. Thus# the enti...

. The recognition of objects and, hence, their descriptions must be grounded in the environment in terms of sensor data. We argue, why the concepts, used to classify perceived objects and used to perform actions on these objects, should integrate action-oriented perceptual features and perception-oriented action features. We present a grounded symbolic representation for these concepts. Moreover, the concepts should be learned. We show a logic-oriented approach to learning grounded concepts. Key Words. Operational concepts, inductive logic programming, combining sensing and action, symbol grounding 1. INTRODUCTION Up to now, application programming of a robot is a time consuming task. The programming is carried out at a very low level. The goal position of the individual commands must be given by exact real world coordinates. This has three undesired consequences. First, even if the new application is very similar to the one before, the control program must be rewritten completely. Se...

There are striking parallels between ecological psychology and the new trends in robotics and computer vision, particularly regarding how agents interact with the environment. We present some ideas from ecological psychology, including control laws using optic flow, affordances and action modes, and describe our implementation of these concepts in a small mobile robot which can avoid obstacles and chase or flee moving targets solely using optic flow. The properties of these methods were further explored in simulation. This work ties in with that of others arguing for a methodological approach in robotics which foregoes a central model/planner. Ecological psychology may not only contribute to robotics, but robotic implementations may in turn provide a test bed for ecological principles and a source of ideas which could be tested in animals and humans. Keywords: ecological psychology, behavior-based robotics, optic flow, obstacle avoidance, tag. ECOLOGICAL ROBOTICS 2 Introduction Over...