13 Items found
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.
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.
How to install a language package and get speech recognition in new languages - As international talking robots, Pepper and NAO can access many languages for speech recognition, and its management is quite easy. This quick how-to explains how to set up new languages installing a language pack in a few simple steps.
Experimenting the flexible and efficient Android library on Pepper’s tablet - Light and flexible, Lottie is a popular mobile library to make 2D animations on Android devices such as Pepper’s tablet. Indeed, Pepper is not just a voice user interface, but the tablet animations are very helpful in improving the interactive efficiency of the robot. At SoftBank Robotics we already tried out Lottie and there is what we found.
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.