A Rotational and Translational Image Stabilization System for Remotely Operated Robots

Remotely operated robots equipped with on board cameras, apart from providing video input to operators, perform optical measurements to assist their navigation as well. Such image processing algorithms require image sequences, free of high frequency unwanted movements, in order to generate their optimal results. Image stabilization is the process which removes the undesirable position fluctuations of a video sequence improving, therefore, its visual quality. In this paper, we introduce the implementation of an image stabilization system that utilizes input from an on board camera and a gyrosensor. The frame sequence is processed by an optic flow algorithm and the inertial data is processed by a discrete Kalman filter. The compensation is performed using two servo motors for the pan and tilt movements and frame shifting for the vertical and horizontal movements. Experimental results of the robot head, have shown fine stabilized image sequences and a system capable of processing 320 times 240 pixel image sequences at approximately 10 frames/sec, with a maximum acceleration of A deg/sec².