Wang Xiaoliang, Jiang Peng, Li Deshi, Sun Tao
Electronic Information School, Wuhan University, Wuhan 430072, China.
GNSS Research Center, Wuhan University, Wuhan 430072, China.
Sensors (Basel). 2017 Sep 19;17(9):2155. doi: 10.3390/s17092155.
Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region.
无人机在数据收集和目标侦察等应用中发挥着重要作用。对于小型无人机而言,精确且最优的路径能够有效提高任务成功率。尽管无人机的路径规划与传统移动机器人的路径规划有相似之处,但无人机的特殊运动学特性(如最小转弯半径)在以往研究中并未得到考虑。在本文中,我们提出了一种用于固定翼无人机的局部可调整、连续曲率、有界路径规划算法。为了解决曲率不连续问题,基于曲率连续性条件的推导,提出了一种最优插值算法和一种关键点偏移算法。为了满足曲率上限并使曲率极值可控,通过将圆弧和具有单调曲率的贝塞尔曲线相结合,设计了一种局部重新规划方案。特别地,在重新规划阶段,以最小曲率圆为规划理念构建了一种路径过渡机制。数值结果表明,该解析规划算法能够有效生成连续曲率路径,同时满足曲率上限约束,并允许无人机在期望的任务区域内通过所有预定义的航路点。