Plane extraction using Point Cloud data for service robot

This paper describes an plane extraction method using point cloud data to perceive an unknown object for a service robot. Recently, depth sensors are used to perceive 3D space for a robot. A depth sensor have been used to recognize unknown environment, such as surface reconstruction, model fitting and so on. Point Cloud Library is typical open source library to deal with 3D point cloud data. However, robot perception for grasping have limitations with high computational costs and low-accuracy for perceiving small objects. Therefore, we propose the PSO-based plane detection method with RG to reconstruct an object from a combination of detected planes. To verify accuracy and computational cost for the plane detection of unknown object, we show that the proposed method has higher accuracy and less computational cost for the proposed method.