グリッパの把持位置推定のための3次元物体認識と面検出

抄録

Service robot arms often need to change tools depending on the object. However, a universal vacuum gripper (UVG) can be used to suck a variety of objects without changing the tool, enabling stable grasping. In this research, we develop a system to recognize and position the object using 3D data obtained from a depth camera and other sensors and to detect the surface that is easy to grip. The goal is a system that directs the robot arm to the optimum grasping point. This paper describes the results of an attempt to implement 3D object recognition and a plane detection function to estimate readily adsorbed surfaces from point cloud data.