用于航点-轨迹优化的受限参数化微分动态程序设计

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Xiaobo Zheng, Feiran Xia, Defu Lin, Tianyu Jin, Wenshan Su, Shaoming He
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引用次数: 0

摘要

无人飞行器(UAV)在执行快递运送、敌情侦察和其他任务时,需要尽快通过多个重要航点,最终到达目标位置。在这类任务中,有两个重要问题需要解决:限制轨迹通过中间航点和优化这些航点之间的飞行时间。针对这两个问题,提出了一种满足多航点约束和航点间自由时间约束的约束参数化微分动态编程(C-PDDP)算法。将中间航点约束视为一种路径状态约束,采用惩罚函数法来约束轨迹通过航点。对于自由时间约束,将航点间的飞行时间转换为时间不变参数,并在航点对应的轨迹时刻进行更新。通过对具有五个不同航点的无人机多点侦察问题进行数值模拟,验证了所提出的 C-PDDP 算法在航点约束和自由时间约束下的有效性。将所提算法与固定时间约束 DDP(C-DDP)进行比较后发现,C-PDDP 可将三段轨迹的飞行时间分别优化为 7.35 秒、9.50 秒和 6.71 秒。此外,C-PDDP 算法优化轨迹航点的最大误差为 1.06 米,远小于用于比较的 C-DDP 算法的误差(7 米)。我们总共模拟了 500 次蒙特卡罗测试,以证明所提出的算法对随机初始猜测的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Constrained Parameterized Differential Dynamic Programming for Waypoint-Trajectory Optimization
Unmanned aerial vehicles (UAVs) are required to pass through multiple important waypoints as quickly as possible in courier delivery, enemy reconnaissance and other tasks to eventually reach the target position. There are two important problems to be solved in such tasks: constraining the trajectory to pass through intermediate waypoints and optimizing the flight time between these waypoints. A constrained parameterized differential dynamic programming (C-PDDP) algorithm is proposed for meeting multiple waypoint constraints and free-time constraints between waypoints to deal with these two issues. By considering the intermediate waypoint constraints as a kind of path state constraint, the penalty function method is adopted to constrain the trajectory to pass through the waypoints. For the free-time constraints, the flight times between waypoints are converted into time-invariant parameters and updated at the trajectory instants corresponding to the waypoints. The effectiveness of the proposed C-PDDP algorithm under waypoint constraints and free-time constraints is verified through numerical simulations of the UAV multi-point reconnaissance problem with five different waypoints. After comparing the proposed algorithm with fixed-time constrained DDP (C-DDP), it is found that C-PDDP can optimize the flight time of the trajectory with three segments to 7.35 s, 9.50 s and 6.71 s, respectively. In addition, the maximum error of the optimized trajectory waypoints of the C-PDDP algorithm is 1.06 m, which is much smaller than that (7 m) of the C-DDP algorithm used for comparison. A total of 500 Monte Carlo tests were simulated to demonstrate how the proposed algorithm remains robust to random initial guesses.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊介绍: ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.
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