Grab a mug - Object detection and grasp motion planning with the Nao robot

Abstract

In this paper we introduce an online grasping system for the Nao robot [1] manufactured by Aldebaran Robotics. The proposed system consists of an object detector and a grasp motion planner. Thereby, known objects are detected by a stereo contour-based object detector and hand motion paths are planned by an A*-based algorithm while avoiding obstacles. Compared to skilled robots such as Justin [2] or ASIMO [3] online grasping with the Nao constitute as particular problem due to the limited processing power and the hand design. The methods proposed allow detecting and grasping objects in real-time on an affordable humanoid robot.