Object recognition using local EGI and 3D models with M-estimators
A robot using a tele-operated system greatly reduces the demands on the human operator, although some human intervention is still required. In order to automate some of the robot's capabilities, we have developed a 3D object-localization method for the robot's positional adjustment. The method is designed to be insensitive to noise and outliers while, at the same time, it has optimal run-time efficiency. Our algorithm is general enough to be applied not only to our dual-armed mobile robots but also to other tele-operation robots. This paper first describes our algorithm, and then presents the performance evaluation.