arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2504.03256eess.SYcs.ROcs.SY

面向控制与规划应用的多旋翼建模的模块化能量感知框架

A Modular Energy Aware Framework for Multicopter Modeling in Control and Planning Applications

Sebastian Gasche, Christian Kallies, Andreas Himmel, Rolf Findeisen

AI总结:

提出一种考虑动力学、能耗和传感器集成的模块化多旋翼建模方法,结合真实试飞数据验证了动力系统与传感器模型,为异构UAS集群的节能路径规划与自主决策奠定基础。

摘要:

无人飞行器(UAVs),尤其是多旋翼飞行器,近年来在监视、监测、检查以及搜救任务中的应用日益普及。其机动性和在受限空间内作业的能力使其在杂乱环境中尤为实用。对于高级控制和任务规划应用而言,对UAVs及其能力进行准确且资源高效的建模至关重要。本研究提出了一种模块化的多旋翼建模方法,综合考虑了飞行器动力学、能耗以及传感器集成。动力系统模型包含了对锂离子电池、电子调速器和无刷直流电机等关键组件的详细描述。这些模型已通过真实试飞数据进行了验证。此外,集成了包括LiDAR和相机在内的传感器模型,以描述监视和监测任务中常用的设备。各个独立模型被组合成一个能量感知的多旋翼模型,这为后续一项关于在杂乱和动态环境中执行搜救任务的无人航空器系统(UAS)集群路径规划的配套研究奠定了基础。这种灵活的建模方法能够轻松描述异构UAS集群中的不同UAVs,从而实现节能运行和自主决策,以确保可靠的任务执行。

英文摘要:

Unmanned aerial vehicles (UAVs), especially multicopters, have recently gained popularity for use in surveillance, monitoring, inspection, and search and rescue missions. Their maneuverability and ability to operate in confined spaces make them particularly useful in cluttered environments. For advanced control and mission planning applications, accurate and resource-efficient modeling of UAVs and their capabilities is essential. This study presents a modular approach to multicopter modeling that considers vehicle dynamics, energy consumption, and sensor integration. The power train model includes detailed descriptions of key components such as the lithium-ion battery, electronic speed controllers, and brushless DC motors. Their models are validated with real test flight data. In addition, sensor models, including LiDAR and cameras, are integrated to describe the equipment often used in surveillance and monitoring missions. The individual models are combined into an energy-aware multicopter model, which provide the basis for a companion study on path planning for unmanned aircaft system (UAS) swarms performing search and rescue missions in cluttered and dynamic environments. The flexible modeling approach enables easy description of different UAVs in a heterogeneous UAS swarm, allowing for energy-efficient operations and autonomous decision making for a reliable mission performance.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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