Robotic Grasping of Unknown Objects

摘要

This work describes the development of a novel vision-based grasping system for unknown objects based on laser range and stereo data. The work presented here is based on 2.5D point clouds, where every object is scanned from the same view point of the laser range and camera position. We tested our grasping point detection algorithm separately on laser range and single stereo images with the goal to show that both procedures have their own advantages and that combining the point clouds reaches better results than the single modalities. The presented algorithm automatically filters, smoothes and segments a 2.5D point cloud, calculates grasping points, and finds the hand pose to grasp the desired object.