Recognition And Tracking Of Micro-sized Robot Based On ORB Feature Points

With the advent of the era of artificial intelligence,mobile robots have been widely used in all aspects of life and production activities.How to improve the accuracy of detection,identification and tracking of robot targets becomes the hotspot of current research.This paper studies the identification and tracking of micro mobile robots in static background.On this basis,the recognition and tracking of micro-robots in dynamic background are also studied.First of all,this paper analyzes the optical flow method in the static background,the background difference method of mixed Gaussian model and the three target detection algorithms of frame difference method.Global motion compensation algorithm based on image block matching in dynamic background.Secondly,the target recognition of the micro-small robot is completed on the basis of detecting the moving target.Detailed analysis of the algorithm principle based on ORB feature point matching recognition.When the matching feature points of micro-robots contain mis-matching points,the RANSAC mis-matching algorithm is analyzed in detail.Aiming at the shortcomings of this algorithm,the RANSAC mismatch matching algorithm based on the spatial consistency criterion is adopted.Then track the moving target,this paper mainly adopts a moving target tracking algorithm based on ORB feature points and Kalman filter.In the case of tracking error,Kalman filter can complete the position correction of micro-small robot to ensure the correctness of the tracking.In order to improve the real-time tracking of micro-mobile robots,Finally,the upper computer video monitoring platform was constructed.The platform uses Microsoft's MFC interface development tools to develop a simple PC monitoring interface.In this interface shows the movement of the micro-robot.And through experiments,the robustness and real-time performance of the detection,recognition and tracking algorithms for micro-robots are verified.This paper proposes an image key frame extraction algorithm based on camera frame acquisition rate and image edge detection algorithm.