Development of the mirror system with humanoid robots

This project focuses in the concept of robot teleoperation and how to make it easier for any type of user. The use of robots requires in most of the cases high knowledge in the area which restrict their use to people specifically prepared for the task. For that reason it is essential for everybody the research for controlling robots using simpler techniques approaching the robotics for everybody. In this project, the user will use the simplest way to control the robot arms and using his/her own arms in the same way that he/she wants to move the robot arms. For reaching that goal, the project assumes the use of Microsoft Kinect device that capture everything the user does. Then a computer will process it and send the information to the robot, in this case a NAO robot. For that reason, the teleoperation is simple and possible even to old people or children. This type of interface opens the door to infinite possibilities and creates a solid foundation on which to establish future knowledge.Ingeniería Informátic

Gaze trajectory prediction in the context of social robotics

Social robotics is an emerging field of robotics that focuses on the interactions between robots and humans. It has attracted much interest due to concerns about an aging society and the need for assistive environments. Within this context, this paper focuses on gaze control and eye tracking as a means for robot control. It aims to improve the usability of human–machine interfaces based on gaze control by developing advanced algorithms for predicting the trajectory of the human gaze. The paper proposes two approaches to gaze-trajectory prediction: probabilistic and symbolic. Both approaches use machine learning. The probabilistic method mixes two state models representing gaze locations and directions. The symbolic method treats the gaze-trajectory prediction problem similar to how word-prediction problems are handled in web browsers. Comparative experiments prove the feasibility of both approaches and show that the probabilistic approach achieves better prediction results

AltURI: a thin middleware for simulated robot vision applications

Fast software performance is often the focus when developing real-time vision-based control applications for robot simulators. In this paper we have developed a thin, high performance middleware for USARSim and other simulators designed for real-time vision-based control applications. It includes a fast image server providing images in OpenCV, Matlab or web formats and a simple command/sensor processor. The interface has been tested in USARSim with an Unmanned Aerial Vehicle using two control applications; landing using a reinforcement learning algorithm and altitude control using elementary motion detection. The middleware has been found to be fast enough to control the flying robot as well as very easy to set up and use