基于深度学习的三维自主避障技术研究

Research on 3D Autonomous Obstacle Avoidance Technology Based on Deep Learning

摘要:

针对自主式潜航器航行中自主规避障碍物传统算法存在的障碍物区域探测精度低、障碍物识别不准确、潜航器航路不最优等问题，采用三维成像声呐和深度学习算法开展了自主规避障碍物优化技术研究， 并通过仿真和漳河水库试验测试了本算法的有效性，可有效提高航行器规避障碍物的成功率和精度，以及 AUV 航行路径优化。

Abstract:

For traditional algorithms of autonomous obstacle avoidance in AUV navigation，there are some problems，such as low detection accuracy of obstacle areas，inaccurate obstacle recognition，and non-optimized AUV route，etc. In this paper，research on optimization technology of autonomous obstacle avoidance is carried out based on 3D imaging sonar and deep learning algorithms. The effectiveness of this algorithm is demonstrated through simulation and test in Zhanghe reservoir. The results show that the success rate and accuracy of AUV obstacle avoidance are significantly improved，and the AUV route is optimized.