The paper discusses dynamics in human-robot interaction. Firstly, we propose a terminology for classifying robot-human interaction dynamics of increasing complexity. Secondly, we address the role of human-robot interaction in a particular application area, namely rehabilitation. Specifically, we discuss the area of autism and how mobile robots can play a therapeutic role in the rehabilitation of children with autism (investigated in the project AURORA). Problems and challenges of this work in progress aiming at `getting the interaction dynamics right' are discussed. 1. Introduction: Building Interactive Robotic Systems In recent years, the concept of believability and believable characters has attracted a lot of attention in the field of autonomous agents ((Bates, 1994), (Dautenhahn, 1998), (Porter and Susman, 2000)). Increasingly, researchers are exploiting techniques which have been originally developed in Arts and animation in order to allow a `suspension of disbelief'....

The new wave of robotics aims to provide robots with the capacity to learn, develop and evolve in interaction with their environments using biologically inspired techniques. This work is placed in perspective by considering its biological and psychological basis with reference to some of the grand theorists of living systems. In particular, we examine what it means to have a body by outlining theories of the mechanisms of bodily integration in multicellular organisms and their means of solidarity with the environment. We consider the implications of not having a living body for current ideas on robot learning, evolution, and cognition and issue words of caution about wishful attributions that can smuggle more into observations of robot behaviour than is scientifically supportable. To round off the arguments we take an obligatory swipe at ungrounded artificial intelligence but quickly move on to assess physical grounding and embodiment in terms of the rooted cognition of the living.

For many years, researchers in the field of mobile robotics have been investigating the use of genetic and evolutionary computation (GEC) to aid the development of mobile robot controllers. Alongside the fundamental choices of the GEC mechanism and its operators, which apply to both simulated and physical evolutionary robotics, other issues have emerged which are specific to the application of GEC to physical mobile robotics. This paper presents a survey of recent methods in GEC-developed mobile robot controllers, focusing on those methods that include a physical robot at some point in the learning loop. It simultaneously relates each of these methods to a framework of two orthogonal issues: the use of a simulated and/or a physical robot, and the use of finite, training phase evolution prior to a task and/or lifelong adaptation by evolution during a task. A list of evaluation criteria are presented and each of the surveyed methods are compared to them. Analyses of the framework and evaluation criteria suggest several possibilities; however, there appear to be particular advantages in combining simulated, training phase evolution (TPE) with lifelong adaptation by evolution (LAE) on a physical robot.

. This paper describes an evolutionary process producing dynamical neural networks used as "brains" for autonomous agents. The main concepts used : genetic algorithms, morphogenesis process, artificial neural networks and artificial metabolism, illustrate our conviction that some fundamental principles of nature may help to design processes from which emerge artificial autonomous agents. The evolutionary process presented here is applied to a simulated autonomous robot. The resulting neural networks are then embedded on a real mobile robot. We emphasize the role of the artificial metabolism and the role of the environment which appear to be the motors of evolution. The first results observed are encouraging and motivate a deeper investigation of this research area. 1 Introduction Most of artificial life researchers try to obtain synthetic forms of organization inspired from biological principles of life. The interdisciplinarity of this research area induces the integration of biologic...

Much recent functional modelling of the central nervous system, beyond traditional “neural net” approaches, focuses on its distributed computational architecture. This paper discusses extensions of our recent work aimed at understanding this architecture from an overall nonlinear stability and convergence point of view, and at constructing artificial devices exploiting similar modularity. Applications to synchronisation and to schooling are also described. The development makes extensive use of nonlinear contraction theory.

Artificial evolution as a design methodology for hardware frees many of the simplifying constraints normally imposed to make design by humans tractable. However, this freedom comes at some cost, and a whole fresh set of issues must be considered. Standard genetic algorithms are not generally appropriate for hardware evolution when the number of components need not be predetermined. The use of simulations is problematic, and robustness in the presence of noise or hardware faults is important. We present theoretical arguments, and illustrate with a physical piece of hardware evolved in the real-world (`intrinsically evolved' hardware). A simple asynchronous digital circuit controls a real robot, using a minimal sensorimotor control system of 32 bits of RAM and a few flip-flops to co-ordinate sonar pulses and motor pulses with no further processing. This circuit is tolerant to single-stuck-at faults in the RAM. The methodology is applicable to many types of hardware, including Field-Programmable Gate Arrays (FPGA's).

This paper is based on the assumption that studies of how humans relate to technology can and should be applied not only to software and interface technology, but also to robots which are increasingly becoming part of our society, e.g. as tools (e.g. service robots such as HelpMate, http://users.ntplx.net/~helpmate/) and toys (e.g. Furby: http://www.game.com/furby/index.html). In order to advance our knowledge on human-robot relationships, this paper reports on an initial study on how people perceive robots. We discuss which concepts may be most usefully adapted from HCI to robotics and present a case study of how people perceive and interact with robots (studying in particular children between the ages of seven and eleven). We hope that over time such research as we present in this paper could provide a development of guidelines for the design of robots for general usage (e.g. service robots). Due to the engineering basis of service robotics most research effort is usually investigated into technical aspects, rather than into HCI and CT related issues. However, the robot's appearance, believability, and above all its social skills needed for interaction and communication with humans in society, are expected to be as important as the robot's technical abilities. A clear example for such demands is the area of rehabilitation robotics where people depend on and interact with machines over long periods of time and often with close physical contact (e.g. the ISAC system which can support sick and physically challenged person, developed at IRL, Vanderbilt University, *

Constructive Biology (as opposed to descriptive biology) means understanding biological mechanisms through building systems that exhibit life-like properties. Applications include learning engineering tricks from biological systems, as well as the validation in biological modelling. In particular, biological systems (unlike reactive robots) in the course of development and experience become temporally grounded. Researchers attempting to transcend mere reactivity have been inspired by the drives, motivations, homeostasis, hormonal control, and emotions of animals. In order to contextualize and modulate behavior, these ideas have been introduced into robotics and synthetic agents, while further flexibility is achieved by introducing learning. Broadening scope of the temporal horizon further requires post-reactive techniques that address not only the action in the now, although such action may perhaps be modulated by drives and affect. Support is needed for expressing and benefitting from...

: We present an architecture to generate behavior for an anthropomorphic robot. The goal is to equip the robot with the capacity to interact with a human. Motivated by the research on biological systems, our basic assumption is that the behavior to perform determines the external and internal structure of the behaving system. We describe the anthropomorphic design of our robot and present a distributed control system that generates human-like navigation and manipulation behavior. As the mathematical framework for this purpose we have developed a control system which is entirely based on dynamical systems in the form of instantiated dynamics and neural fields. We also present a dynamic scheme for behavioral organization based on competitive dynamics. 1 Introduction The behavior of living organisms is based on their own sensory information. As the acquisition of sensor information is an active process which changes the state of the system within the environment, the behaving system dir...

representational knowledge is avoided. Creating and maintaining accurate representations of the world is a time-consuming error-prone process. Purely reactive systems do not maintain world models, instead reacting directly to the stimuli the world presents. This is particularly useful in highly dynamic and hazardous worlds, where the environment is unpredictable and potentially hostile. 3. Animal models of behavior are often used as a basis for these systems. Models from neuroscience, cognitive psychology, and ethology are used to capture the nature of the behaviors that are necessary for a robot's safe interaction with a hostile world. Reactive Robotic Systems 3 4. Demonstrable robotic results have been achieved. These techniques have been applied to a wide range of robots including six-legged walking robots, pipe-crawling robots, robots for indoor/outdoor activities, mobile manipulators, dextrous hands, and entire herds of mobile robots. As these systems are highly modular, they...