论文标题
在动态环境中，微型航空车的基于强大的基于视力的障碍
Robust Vision-based Obstacle Avoidance for Micro Aerial Vehicles in Dynamic Environments
论文作者
论文摘要
在本文中，我们提出了一种基于机上视觉的方法，以避免在动态环境中移动障碍。我们的方法依赖于基于深度图像对的有效障碍物检测和跟踪算法，该算法对估计位置，速度和障碍物的大小。通过制定偶然限制的模型预测控制器（CC-MPC）来确保微型航空车辆（MAV）（MAV）之间的碰撞概率和每个移动障碍物在指定的阈值以下来实现强大的碰撞避免。该方法考虑了MAV动态，状态估计和障碍感知不确定性。所提出的方法是在配备立体声摄像机的四极管上实现的，并在各种环境中进行了测试，显示出有效的在线碰撞避免移动障碍物。
In this paper, we present an on-board vision-based approach for avoidance of moving obstacles in dynamic environments. Our approach relies on an efficient obstacle detection and tracking algorithm based on depth image pairs, which provides the estimated position, velocity and size of the obstacles. Robust collision avoidance is achieved by formulating a chance-constrained model predictive controller (CC-MPC) to ensure that the collision probability between the micro aerial vehicle (MAV) and each moving obstacle is below a specified threshold. The method takes into account MAV dynamics, state estimation and obstacle sensing uncertainties. The proposed approach is implemented on a quadrotor equipped with a stereo camera and is tested in a variety of environments, showing effective on-line collision avoidance of moving obstacles.
