论文标题
可行的计算高效路径规划无人用碰撞避免
Feasible Computationally Efficient Path Planning for UAV Collision Avoidance
论文作者
论文摘要
本文介绍了无人驾驶飞机（UAV）的强大计算有效的实时避免算法，即基于记忆的人工势场（MWF-APF）方法。新算法在壁挂方法（WFM）和人工电位方法（APF）之间开关，具有提高情况意识能力。考虑历史轨迹以避免重复的错误决定。此外，它可以有效地应用于具有低计算能力的平台。例如，采用配备有限的飞行时间（TOF）测距仪的四轮旋翼，以验证该算法的有效性和效率。已经进行了软件模拟和物理飞行测试，以证明在复杂方案中MWF-APF方法的能力。
This paper presents a robust computationally efficient real-time collision avoidance algorithm for Unmanned Aerial Vehicle (UAV), namely Memory-based Wall Following-Artificial Potential Field (MWF-APF) method. The new algorithm switches between Wall-Following Method (WFM) and Artificial Potential Field method (APF) with improved situation awareness capability. Historical trajectory is taken into account to avoid repetitive wrong decision. Furthermore, it can be effectively applied to platform with low computing capability. As an example, a quad-rotor equipped with limited number of Time-of-Flight (TOF) rangefinders is adopted to validate the effectiveness and efficiency of this algorithm. Both software simulation and physical flight test have been conducted to demonstrate the capability of the MWF-APF method in complex scenarios.
