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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.robot.2009.03.013 Byline: Fabio Dalla Libera (a), Takashi Minato (b), Ian Fasel (d), Hiroshi Ishiguro (c)(b), Enrico Pagello (a), Emanuele Menegatti (a) Abstract: Most humanoid soccer robot teams design the basic movements of their robots, like walking and kicking, off-line and manually. Once these motions are considered satisfactory, they are stored in the robot's memory and played according to a high level behavioral strategy. Much time is spent in the development of the movements, and despite the significant progress made in humanoid soccer robots, the interfaces employed for the development of motions are still quite primitive. In order to accelerate development, an intuitive instruction method is desired. We propose the development of robot motions through physical interaction. In this paper we propose a 'teaching by touching' approach; the human operator teaches a motion by directly touching the robot's body parts like a dance instructor. Teaching by directly touching is intuitive for instructors. However, the robot needs to interpret the instructor's intention since tactile communication can be ambiguous. This paper presents a method to learn the interpretation of the touch meaning and investigates, through experiments, a general (shared among different users) and intuitive touch manner. Author Affiliation: (a) Intelligent Autonomous Systems Laboratory, Department of Information Engineering (DEI), Faculty of Engineering, University of Padua, Via Gradenigo 6/a, I-35131 Padua, Italy (b) ERATO, Japan Science and Technology Agency, Osaka University, Suita, Osaka, 565-0871, Japan (c) Department of Adaptive Machine Systems, Osaka University, Suita, Osaka, 565-0871, Japan (d) The University of Texas at Austin, Department of Computer Sciences, 1 University Station C0500, Taylor Hall 2.124, Austin, USA

We have incorporated robots into the introductory undergraduate physics laboratory to introduce a creative component and to show some applications of physics principles in a way that strongly engages student interest. We have developed low-cost mobile platforms and navigation methods suitable for large numbers of introductory level students. Radio remote control was the dominant navigation method implemented in the classroom, but autonomous navigation was also achieved. We discuss robot construction, the organization of the lab, student reactions, and our experiences in sustaining the program. [DOI: 10.1119/1.2942413]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.robot.2007.05.005 Byline: M. Rodriguez (a), R. Iglesias (a), C.V. Regueiro (b), J. Correa (a), S. Barro (a) Abstract: Research on robot techniques that are fast, user-friendly, and require little application-specific knowledge by the user, is more and more encouraged in a society where the demand of home-care or domestic-service robots is increasing continuously. In this context we propose a methodology which combines reinforcement learning and genetic algorithms to teach a robot how to perform a task when only the specification of the main restrictions of the desired behaviour is provided. Through this combination, both paradigms must be merged in such a way that they influence each other to achieve a fast convergence towards a good robot-control policy, and reduce the random explorations the robot needs to carry out in order to find a solution. Another advantage of our proposal is that it is able to easily incorporate any kind of domain-dependent knowledge about the task. This is very useful for improving a robot controller, for applying a robot-controller to move a different robot-platform, or when we have certain 'feelings' about how the task should be solved. The performance of our proposal is shown through its application to solve a common problem in mobile robotics. Author Affiliation: (a) Electronics and Computer Science, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain (b) Department of Electronic and Systems, University of CoruA[+ or -]a, 15701, A CoruA[+ or -]a, Spain

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.robot.2006.04.015 Byline: Ulrich Nehmzow (a), Roberto Iglesias (b), Theocharis Kyriacou (a), Stephen A. Billings (c) Abstract: The operation of an autonomous mobile robot in a semi-structured environment is a complex, usually non-linear and partly unpredictable process. Lacking a theory of robot-environment interaction that allows the design of robot control code based on theoretical analysis, roboticists still have to resort to trial-and-error methods in mobile robotics. The RobotMODIC project aims to develop a theoretical understanding of a robot's interaction with its environment, and uses system identification techniques to identify the system robot-task-environment. In this paper, we present two practical examples of the RobotMODIC process: mobile robot self-localisation and mobile robot training to achieve door traversal. In both examples, a transparent mathematical function is obtained that maps inputs-sensory perception in both cases-to output -- location and steering velocity respectively. Analysis of the obtained models reveals further information about the way in which a task is achieved, the relevance of individual sensors, possible ways of obtaining more parsimonious models, etc. Author Affiliation: (a) Department of Computer Science, University of Essex, Colchester CO4 3SQ, UK (b) Department of Electronics and Computer Science, University of Santiago de Compostela, Spain (c) Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK Article History: Received 19 December 2005; Revised 6 March 2006; Accepted 6 April 2006

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.robot.2004.07.002 Byline: Yu Ogura (a), Shumpei Ando (a), Hun-ok Lim (b)(c), Atsuo Takanishi (a)(c) Keywords: Biped humanoid robot; Walking instruction; Walkin pattern generation Abstract: This paper describes a sensory-based biped walking motion instruction strategy. Visual and auditory sensors are employed to generate walking patterns according to human orders and to memorize various complete walking patterns effectively and systematically. The motion of lower-limbs for locomotion is created by an online pattern generator based on the sensory information. At the same time, the motion of the trunk and the waist for stability is generated online by a balance control method. Combining these locomotive and balance motions, a complete walking pattern is hierarchically constructed and memorized on a database. The walking instruction is conducted through computer simulation, and its effectiveness is verified. Author Affiliation: (a) Graduate School of Science and Engineering, Waseda University, 3-4-1 Ohkubo, Shinjuku-ku, Tokyo 169-8555, Japan (b) Department of System Design Engineering, Kanagawa Institute of Technology, 1030 Shimoogino, Atsugi-shi, Kanagawa 243-0292, Japan (c) Humanoid Robotics Institute, Waseda University, 17 Kikui-cho, Shinjuku-ku, Tokyo 162-0044, Japan

Robotic hardware and software prices are continuing to come down, and as one consequence, undergraduate-level, hands-on robotics courses are increasingly available. Depending on a professor's preferences, robotics courses emphasize mechanics, electronics, or programming.

This paper presents detailed description of a laboratory simulator that uses two robots fixed on earth to simulate the motion of a robot in space relative to a free-flying target. This simulator is appealing because it creates an environment on earth similar to what an astronaut observes watching from the space shuttle. Therefore, it could be a valuable tool for training of astronauts on earth. Also, this simulator uses off-the-shelf industrial robots in contrast to laboratory facilities today that use special designs of robots to achieve this same task. The proposed simulator can be valuable for studying real-time motion in space and in evaluating the effectiveness of onboard sensors and control systems. The objectives of this paper are to: i) describe the laboratory setup, ii) present the computational details of this simulator, iii) estimate the computation needs of this simulator, and iv) present a computer implementation of this simulator using two KUKA robots.