RoboCup Soccer Leagues

RoboCup was created in 1996 by a group of Japanese, American, and European Artificial Intelligence and Robotics researchers with a formidable, visionary long-term challenge: “By 2050 a team of robot soccer players will beat the human World Cup champion team.” At that time, in the mid 90s, when there were very few effective mobile robots and the Honda P2 humanoid robot was presented to a stunning public for the first time also in 1996, the RoboCup challenge, set as an adversarial game between teams of autonomous robots, was fascinating and exciting. RoboCup enthusiastically and concretely introduced three robot soccer leagues, namely “Simulation,” “Small-Size,” and “Middle-Size,” as we explain below, and organized its first competitions at IJCAI’97 in Nagoya with a surprising number of 100 participants [RC97]. It was the beginning of what became a continously growing research community. RoboCup established itself as a structured organization (the RoboCup Federation www.RoboCup.org). RoboCup fosters annual competition events, where the scientific challenges faced by the researchers are addressed in a setting that is attractive also to the general public. and the RoboCup events are the ones most popular and attended in the research fields of AI and Robotics.RoboCup further includes a technical symposium with contributions relevant to the RoboCup competitions and beyond to the general AI and robotics.

Generating timed trajectories foran autonomous robot

Tese de Doutoramento Programa Doutoral em Engenharia Electrónica e Computadores

The potential field method and the nonlinear attractor dynamics approach: what are the differences?

One of the most popular approaches to path planning and control is the potential field method. This method is particularly attractive because it is suitable for on-line feedback control. In this approach the gradient of a potential field is used to generate the robot's trajectory. Thus, the path is generated by the transient solutions of a dynamical system. On the other hand, in the nonlinear attractor dynamic approach the path is generated by a sequence of attractor solutions. This way the transient solutions of the potential field method are replaced by a sequence of attractor solutions (i.e., asymptotically stable states) of a dynamical system. We discuss at a theoretical level some of the main differences of these two approaches.

Development of autonomous maintenance in a furniture company

This article presents a work performed in the maintenance department of a furniture company in Portugal, in order to develop and implement autonomous maintenance. The main objective of the project was related to the objective to increase and make effective the autonomous maintenance tasks performed by production operators, and in this way avoiding unplanned downtime due to equipment failures. Although some autonomous maintenance tasks were already carried out within the company, a preliminary study revealed weaknesses in the application of this tool. In the initial phase of this pilot project, the main problems encountered at the level of autonomous maintenance were related to the lack of time to carry out these tasks, showing that the stipulated procedures were far from the real needs of the company. To solve these problems a pilot project was conducted, making several changes in the performance of autonomous maintenance tasks, making them standard and adapted to reality of each production line. There was a general improvement in the factory indicators, and essentially there was a behavioral change, since the operators felt that their opinions were taking into account and began to understand the importance of small tasks performed by them.

Towards human-like bimanual movements in anthropomorphic robots: a nonlinear optimization approach

Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.