Abstract
It is important for service robots to recognize human activity. A table is the center of human life. Objects on the table are changed by human. Therefore service robots need to find objects on the table and detect changes. This paper describes an observation system of tabletop objects. Our system includes a perceptual pipeline of RGB-D point cloud and a planning of the location to observe a table. In addition, the location of objects, and their identities are recorded in the database. This system is useful for any application that involves dealing with objects, including grasping, change detection, and object search. We demonstrate a robot equipped with a Microsoft Kinect RGB-D sensor and a Velodyne HDL-32E Lidar sensor build on our system.
