基于四旋翼无人机平台的实时多目标检测算法

随着无人机技术和深度学习技术的发展,基于深度学习的多目标检测算法在工业无人机中得到了广泛的应用。针对目前基于深度学习的多目标检测算法占用大量计算量资源,难以在算力有限的中小型无人机平台上实时运行的问题,分析了深度学习算法在低功耗CPU上的耗时,提出一种卷积神经网络计算优化方法。在机载计算机中进行仿真,结果表明在检测效果基本不变的条件下,算法帧率达到了56FPS,实现了无人机平台上的实时多目标检测。

Real-Time Multi-Target Detection Algorithm on Quadrotor Platform

The development of quadrotor drone and deep learning, target detection algorithms based on deep learning have been widely used in the drone industry. Existing deep learning-based detection algorithms cannot be run in real time on drone onboard computer with limited computing resources. This paper analyzesd the distribution of run time of deep learning algorithm on low power CPU, and proposed a computational optimization method for convolutional neural networks. The experimental results in drone onboard computer show that the detection speed can reach 56 FPS while the detection result keeps unchanged.