Teleworkbench: An Analysis Tool for Multi-Robotic Experiments

Tanoto A, Du JL, Witkowski U, Rückert U. Teleworkbench: An Analysis Tool for Multi-Robotic Experiments. In: Proceedings of the IFIP Conference on Biologically Inspired Cooperative Computing (BICC 2006), 19th World Computer Congress (WCC). Santiago, Chile; 2006.This paper presents a tool, one component of the Teleworkbench system, for analyzing experiments in multi-robotics. The proposed tool combines the video taken by a web cam monitoring the field where the experiment runs and some computer generated visual objects representing important events and information as well as robots’ behavior into one interactive video based on MPEG-4 standard. Visualization and data summarization enables the developer to quickly grasp a situation, whereas the possibility of scrolling through the video and selectively activating information helps him analyzing interesting events in depth. Because of the MPEG-4 standard used for the output video, the analysis process can be done in a wide range of platforms. This trait is beneficial for education and research cooperation purposes

Teleworkbench: an analysis tool for multi-robotic experiments

This paper presents a tool, one component of the Teleworkbench system, for analyzing experiments in multi-robotics. The proposed tool combines the video taken by a web cam monitoring the field where the experiment runs and some computer generated visual objects representing important events and information as well as robots’ behavior into one interactive video based on MPEG-4 standard. Visualization and data summarization enables the developer to quickly grasp a situation, whereas the possibility of scrolling through the video and selectively activating information helps him analyzing interesting events in depth. Because of the MPEG-4 standard used for the output video, the analysis process can be done in a wide range of platforms. This trait is beneficial for education and research cooperation purposes.1st IFIP International Conference on Biologically Inspired Cooperative Computing - Robotics and Sensor NetworksRed de Universidades con Carreras en Informática (RedUNCI

Exploiting opponent behavior in multi-agent systems

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201

Advances in Reinforcement Learning

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic