10 Items found
An international partnership where SBRE puts forward Pepper to answer user specific needs - How can technology support the worldwide issue of the ageing populations and the complexity of human connections? SBRE committed into the CARESSES program to integrate a system that plans the robot's actions according to a relevant cultural knowledge base.
CROWDBOT, an European Collaborative project enables robots to freely navigate and assist humans in crowded areas. - Today’s moving robots stop when a human, or any obstacle is too close, to avoid impact. This prevents robots from entering packed areas and effectively performing in a high dynamic environment. CROWDBOT aims to fill in the gap in knowledge on close interactions between robots and humans in motion.
We made Pepper the robot play games of skill with AI (Artificial Intelligence) at SBRE - SBRE AI Lab (Artificial Intelligence Laboratory) taught Pepper how to successfully throw a ball in a cup and a dart at the dartboard (they are exactly the same dynamic problem) using dexterity and a bit of dynamical systems theory. Here is the story of what it takes to match elementary games and robotics.
How to add a desktop shortcut on Gnome 3 to launch Android Studio (Ubuntu 16.04) - This tip explains two ways to add a desktop icon to launch Android Studio from a Gnome 3 environment: activate or create icons on the desktop.
How to add a launcher shortcut on Gnome 3 to launch Android Studio (Ubuntu 16.04) - This tip explains how to add a shortcut to the app launcher to launch Android Studio on Ubuntu.
A Research project about Pepper and NAO immersive teleoperation - A new immersive teleoperation solution based on Extreme Learning Machine (ELM), a Machine Learning technique, is introduced for Pepper and NAO robots. Immersive teleoperation is defined as a robot remote control that renders the operator the sensation of being inside the teleoperated environment and providing a feeling of being the robot itself. The solution is independent of other mapping approaches (e.g. inverse kinematics) and the user’s whole body is used for the robot control. Even with scarce training data, the solution returns satisfactory results in both precision and computational speed.