电光与控制, 2017, 24 (12): 31, 网络出版: 2021-01-22
基于立体视觉和光流的无人机避障算法研究
Stereo Vision and Optical Flow Based Obstacle Avoidance Algorithm for UAVs
摘要
无人机在飞行过程中必须能够检测障碍物并且准确躲避。为使无人机在飞行过程中更加安全, 提出了一种双目立体视觉和光流相结合的避障方法。双目立体视觉通过边缘索引算法来获取可靠的视差值, 并根据视差线汇聚角度得到空间深度信息, 进而辨别物体的远近; 基于SIFT的光流法能得到障碍物相对于摄像头的每一个时刻的运动速度。为了更快地得到更加准确的位置信息, 将立体视觉和光流结合在一起。实验结果表明, 该方法能有效提高避障的效率和精度。
Abstract
UAVs must be able to detect obstacles during flight and avoid the obstacles precisely.In order to make the UAV safer in flight, a method of obstacle avoidance is proposed combining binocular stereoscopic vision with optical flow.The binocular stereoscopic vision is used to obtain reliable parallax value through edge index algorithm, to get the spatial depth information according to the parallax convergence angle, thus to identify the object distance.The SIFT based optical flow method can obtain the movement speed of the obstacle relative to the camera at each moment.In order to obtain more accurate position information more quickly, the stereoscopic vision and optical flow are combined together.The experimental results show that this method can effectively improve the efficiency and precision of obstacle avoidance.
朱平, 甄子洋, 覃海群, 江驹. 基于立体视觉和光流的无人机避障算法研究[J]. 电光与控制, 2017, 24(12): 31. ZHU Ping, ZHEN Zi-yang, QIN Hai-qun, JIANG Ju. Stereo Vision and Optical Flow Based Obstacle Avoidance Algorithm for UAVs[J]. Electronics Optics & Control, 2017, 24(12): 31.