A collision avoidance system based on simple digital cameras would help enable the safe integration of small UAVs into crowded, low-altitude environments. In this work, we present an obstacle avoidance system for small UAVs that uses a monocular camera with a hybrid neural network and path planner controller. The system is comprised of a vision network for estimating depth from camera images, a high-level control network, a collision prediction network, and a contingency policy. This system is evaluated on a simulated UAV navigating an obstacle course in a constrained flight pattern. Results show the proposed system achieves low collision rates while maintaining operationally relevant flight speeds.

翻译：以简单数字相机为基础的避免碰撞系统将有助于小型无人驾驶航空器安全地融入拥挤、低高度的环境。在这项工作中,我们为使用带有混合神经网络和路径规划控制器的单镜相机的小型无人驾驶航空器提供了一个避免碰撞系统。该系统由用于估计摄影图像深度的视觉网络、高水平控制网络、碰撞预测网络和应急政策组成。该系统是在一个模拟无人驾驶航空器在受限制的飞行模式下沿障碍道飞行时进行评估的。结果显示,拟议的系统在保持与操作相关的飞行速度的同时实现了低碰撞率。