Research on Obstacle Avoidance Technology of Indoor Robots Based on Optical Flow and Feature Extraction
In order to solve the forward obstacle avoidance problem of indoor robots,a visual obstacle a-voidance method based on optical flow and feature extraction is proposed.LK optical flow is combined with multi-scale thought,and affine transformation is added to improve the noise robustness of tracking corner points,so as to accurately detect obstacles in the field of view.By assessing the risk degree of obstacles,a collision mechanism based on collision time(TTC)combined with an optical flow balancing strategy was developed to guide the robot to move on a collision-free path.The combination of improved optical flow and feature extraction can improve the tracking success rate of the camera under fast motion,and the collision strategy formulated can effectively avoid the obstacles in front of the robot.Experiments show that the algo-rithm can improve tracking accuracy,effectively detect obstacles in the field of view,and guide the robot to drive without collision when the camera moves quickly,with strong independence and real-time performance.
NETL
NSTL
万方数据
