Roboter lernen mit Gegenständen umzugehen: neue Entwicklungen und Chancen

Abstract

Experts predict that future robot applications will require safe and predictable operation: robots will need to be able to explain what they are doing to be trusted. To reach this goal, they will need to perceive their environment and its object to understand better the world and task they have to perform. This article gives an overview of present advances with the focus on options to model, detect, classify, track, grasp and manipulate objects. With the approach of colour and depth (RGB-D) cameras and the approaches in deep learning, robot vision was pushed considerably over the last years. It is possible to model and recognise objects, though prove in industrial settings is yet outstanding. Given a first detection of larger structures such as tables, chairs or assembly places, relations between object and setting can be obtained leading to a first interpretation of the scenes. We highlight present developments and point out future developments towards service and industrial robotics applications.