Implementation of real-time object recognition system for home-service robot by integrating SURF and BRISK

This paper proposes a real-time object recognition systems for recognizing known objects and searching unknown objects for home service robot. The object recognition system is mainly used in recognizing known objects, which combined Compute Unified Device Architecture (CUDA), Speeded Up Robust Features (SURF) detector and Binary Robust Invariant Scalable Keypoints (BRISK) descriptor for improving the computation speed and decreasing the consumption on memory. On the other side, the visual perception system is usually used for searching unknown objects, which calculated the depth differences and found the contours of objects. The experimental results in the laboratory and the competition in robot@home league at RoboCup Japan Open 2013 Tokyo illustrate that the robot can successfully real-time recognize the known objects and search the unknown objects.