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Terrestrial Testing of Multi-Agent, Relative Guidance, Navigation, and Control Algorithms

机译:多智能体的地面测试,相对制导,导航和控制算法

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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.
机译:小型分布式卫星应用的兴起导致人们对多主体,协作制导,导航和控制(GNC)策略的兴趣日益浓厚。为了集成和测试与多主体协作环境相关的算法,开发了协作自主网络系统(CANS)实验室。带有板载传感器套件的多个三轮全向地面机器人可以在进行硬件在环测试的同时保持平面相对动态。已经建立了软件框架,以使用Clohessy-Wiltshire-Hill(CWH)动力学进行精确的动力学仿真。在本文中,通过使用示例编队飞行应用程序(包含不确定的场景参数)演示了CANS实验室。

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