多智能体、相对制导、导航和控制算法的地面测试

Mark Mercier, S. Phillips, Matt Shubert, Wenjie Dong
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引用次数: 1

摘要

小型、分布式卫星应用的增加导致对多智能体、协作制导、导航和控制(GNC)策略的兴趣增加。为了集成和测试与多智能体协作环境相关的算法,开发了协作自治网络系统(CANS)实验室。带有机载传感器套件的多个三轮全方位地面机器人可以在坚持平面相对动力学的同时进行硬件在环测试。建立了一个软件框架,可以使用Clohessy-Wiltshire-Hill (CWH)动力学进行精确的动力学模拟。本文通过一个包含不确定场景参数的编队飞行应用实例,对can实验室进行了演示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Terrestrial Testing of Multi-Agent, Relative Guidance, Navigation, and Control Algorithms
The rise in small, distributed satellite applications has led to an increased interest in multi-agent, cooperative guidance, navigation, and control (GNC) strategies. In order to integrate and test algorithms associated with a multi-agent cooperative environment, the Cooperative Autonomous Networked Systems (CANS) Lab was developed. Multiple three-wheeled, omni-directional ground robots with on-board sensor suites enable hardware-in-the-loop testing while adhering to planar relative dynamics. A software framework has been established to enable accurate dynamics simulation using Clohessy-Wiltshire-Hill (CWH) dynamics. In this paper, the CANS lab is demonstrated through the use of an example formation flying application which incorporates uncertain scenario parameters.
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