Learning provides a useful tool for the automatic design of autonomous robots. Recent research on learning robot control has predominantly focussed on learning single tasks that were studied in isolation. If robots encounter a multitude of control learning tasks over their entire lifetime, however, there is an opportunity to transfer knowledge between them. In order to do so, robots may learn t...

This paper proposes a new selection mechanism in evolutionary learning for fuzzy systems, which is applied to the learning of shooting action for robot soccer. In generic evolutionary algorithm, since the evaluation and the selection are performed on the level of chromosome, selected chromosome may include non-effective or bad genes, which increase the uncertainty of the solutions. To solve thi...

For developing usable service robots, deeper knowledge about how the robot should cope with many situations is essential. We suggest some behavioral goals for better communication with network based entertainment robots. First, the robot should show diverse behaviors. Second, the diverse behaviors should be coherent with some traits of personality. Finally, the behaviors or responses of the rob...

Deciphering the behaviour of intelligent others is a fundamental characteristic of our own intelligence. As we interact with complex intelligent artefacts, humans inevitably construct mental models to understand and predict their behaviour. If these models are incorrect or inadequate, we run the risk of self deception or even harm. This paper reports progress on a programme of work investigatin...

The problem of defining robot behaviors to completely address a large and complex set of situations is very challenging. We present an approach for robot’s action selection in the robot soccer domain using Case-Based Reasoning techniques. A case represents a snapshot of the game at time t and the actions the robot should perform in that situation. We basically focus our work on the retrieval an...

The Autonomous City Explorer (ACE) project aims to create a robot capable of navigating unknown urban environments without the use of GPS data or prior map knowledge. The robot finds its way by interacting with pedestrians and building a topological representation of its surroundings. This paper outlines the necessary ingredients for successful low-level navigation on sidewalks, information ret...

This paper examines the problem of how a mobile robot may coordinate among multiple, possibly conflicting deliberative processes for reasoning about object interactions in a soccer domain. This paper frames deliberative coordination as an instance of the algorithm selection problem and describes a novel framework by which a mobile robot may learn to coordinate its deliberative reasoning in resp...

This paper discusses the design concept and system development of a small and relatively fast walking, autonomous humanoid robot with 17 degrees-offreedom (DoF). The selection of motor size and gear ratios is based on numerical optimization of detailed multibody dynamics and optimal control corresponding to fast steps of the robot with an envisioned target speed of more than 0.5m/s. In this pap...

Intelligent autonomous robotics is a promising area with many potential applications that could benefit from non-traditional models of computation. Information processing systems interfaced with the real world must deal with a continuous and uncertain environment, and must cope with interactions across a range of time-scales. Robotics problems resist existing tools and, consequently, new perspe...

The physical appearance and behavior of a robot is an important asset in terms of Human-Computer Interaction. Multimodality is also fundamental, as we humans usually expect to interact in a natural way with voice, gestures, etc. People approach complex interaction devices with stances similar to those used in their interaction with other people. In this paper we describe a robot head, currently...