Efficient 3D object perception and grasp planning for mobile manipulation in domestic environments

In this article, we describe efficient methods for tackling everyday mobile manipulation tasks that require object pick-up. In order to achieve real-time performance in complex environments, we focus our approach on fast yet robust solutions. For 3D perception of objects on planar surfaces, we develop scene segmentation methods that process depth images in real-time at high frame rates. We efficiently plan feasible, collision-free grasps for the segmented objects directly from the perceived point clouds to achieve fast execution times. We evaluate our approaches quantitatively in lab experiments and also report on the successful integration of our methods in public demonstrations at RoboCup@Home competitions in 2011 and 2012.

► Efficient techniques for mobile manipulation in domestic environments.
► Real-time perception of objects using depth cameras.
► Efficient grasp planning on partial views.
► Experiments and public demonstrations to validate the approach.