论文标题
运动型轨迹的运动轨迹轨迹的运动轨迹轨迹无人机的时间优势轨迹
Kinematic Orienteering Problem With Time-Optimal Trajectories for Multirotor UAVs
论文作者
论文摘要
在许多无人驾驶飞机（UAV）用于监视和数据收集的申请中，由于给定的最大飞行时间，无法到达所有要求的位置。因此，必须优先考虑请求的位置，并且选择最重要的位置的问题被建模为定向问题（OP）。为了在这种情况下充分利用无人机的运动学特性，我们将OP与时间优化轨迹的产生与速度和加速度的边界相结合。我们将最终的问题定义为运动学定向问题（KOP），并提出了一种精确的混合企业配方，并作为启发式解决方案方法以及大型邻里搜索（LNS）。我们根据文献和基准的定向启动实例证明了我们的方法的有效性，以针对Dubins定向培训问题（DOP）的最佳解决方案作为最先进的解决方案。此外，我们通过仿真\ color {black}显示所得解决方案可以通过现代基于MPC的飞行控制器精确跟踪。由于我们证明在多个维度上生成时间优势轨迹的最新轨迹通常不正确，因此我们进一步提出了一种改进的时间 - 最佳轨迹生成的分析方法。
In many unmanned aerial vehicle (UAV) applications for surveillance and data collection, it is not possible to reach all requested locations due to the given maximum flight time. Hence, the requested locations must be prioritized and the problem of selecting the most important locations is modeled as an Orienteering Problem (OP). To fully exploit the kinematic properties of the UAV in such scenarios, we combine the OP with the generation of time-optimal trajectories with bounds on velocity and acceleration. We define the resulting problem as the Kinematic Orienteering Problem (KOP) and propose an exact mixed-integer formulation together with a Large Neighborhood Search (LNS) as a heuristic solution method. We demonstrate the effectiveness of our approach based on Orienteering instances from the literature and benchmark against optimal solutions of the Dubins Orienteering Problem (DOP) as the state-of-the-art. Additionally, we show by simulation \color{black} that the resulting solutions can be tracked precisely by a modern MPC-based flight controller. Since we demonstrate that the state-of-the-art in generating time-optimal trajectories in multiple dimensions is not generally correct, we further present an improved analytical method for time-optimal trajectory generation.
