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首页> 外文期刊>Journal of Intelligent & Robotic Systems: Theory & Application >Guidance-Control System of a Quadrotor for Optimal Coverage in Cluttered Environment with a Limited Onboard Energy: Complete Software
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Guidance-Control System of a Quadrotor for Optimal Coverage in Cluttered Environment with a Limited Onboard Energy: Complete Software

机译:电流调节器的指导控制系统,用于杂乱环境中的最佳覆盖,具有有限的衬垫能量:完整的软件

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In this paper, a Guidance-Control System (GCS) for optimal coverage planning, using a quadrotor, in damaged area is considered. The quadrotor is assumed to visit a set of reachable points, defined manually by the user or automatically generated, following the shortest path while avoiding the no-fly zones. The problem is solved by using a two-stage proposed algorithm. In the first stage, a novel tool for cluttered environments based on optimal Rapidly-exploring Random Trees (RRT) approach, called Multi-RRT* Fixed Node (RRT*FN), is developed to define the shortest paths from each point to its neighbors. By means of the pair-wise costs between points provided by the first-stage algorithm, in the second stage, the overall shortest path is obtained by solving a Traveling Salesman Problem (TSP) using Genetic Algorithms (GA). Taking into consideration the limited onboard energy, multi-rounds for the coverage planning are assumed as an alternative by adapting our problem as a Vehicle Routing Problem (VRP). This latter is solved using the savings heuristic approach. The guidance module is supported by an efficient controller that minimizes the consumed energy and allows a damped response (i.e. without overshoot). It is a reference model based control strategy called Interconnection Damping Assignment-Passivity Based Control (IDA-PBC). The effectiveness of the overall system is demonstrated via numerical simulations and confirmed experimentally with very promising results.
机译:在本文中,考虑了使用四轮机会在损坏区域中的最佳覆盖计划的指导控制系统(GCS)。假设Quadrotor访问一组可达点,由用户手动定义或在避免空缺区域时自动生成。使用两阶段提出的算法来解决问题。在第一阶段,基于最佳快速探索的随机树(RRT)方法(称为多RRT *固定节点(RRT * Fn)的新颖的环境工具,以便为其邻居定义每个点的最短路径。借助于通过第一阶段算法提供的点之间的成本,在第二阶段,通过使用遗传算法(GA)解决行驶推销员问题(TSP)来获得整体最短路径。考虑到有限的板载能量,通过将问题作为车辆路由问题(VRP),假设覆盖计划的多轮作为替代方案。这种后者使用储蓄启发式方法解决了。引导模块由高效控制器支持,可最大限度地减少消耗的能量并允许阻尼响应(即,没有过冲)。它是一种基于参考模型的控制策略,称为互连阻尼分配基于基于控制的控制(IDA-PBC)。通过数值模拟证明整个系统的有效性并通过非常有前途的结果实验证实。

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