Unknown object extraction based on plane detection in 3D space

This paper describes an unknown object extraction based on plane detection for an intelligent robot using a 3D range sensor. Previously, various methods have been proposed to perceive unknown environments. However, conventional unknown object extraction methods need predefined knowledge, and have limitations with high computational costs and low-accuracy for small object. In order to solve these problems, we propose an online processable unknown object extraction method based on 3D plane detection. To detect planes in 3D space, we have proposed a simple plane detection that applies particle swarm optimization (PSO) with region growing (RG), and integrated object plane detection. The simple plane detection is focused on small plane detection and on reducing computational costs. Furthermore, integrated object plane detection focuses on the stability of the detecting plane. Our plane detection method can detect a lot of planes in sight. This paper proposes an object extraction method which is grouped some planes according to the relative position. Through experiment, we show that unknown objects are extracted with low computational cost. Moreover, the proposed method extracts some objects in complicated environment.