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Integrated navigation of aerial robot for GP and GP-denied environment

机译:用于GP和GP拒绝环境的空中机器人的综合航行

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In this study, novel robust navigation system for aerial robot in GPS and GPS-denied environments is proposed. Generally, the aerial robot uses position and velocity information from Global Positioning System (GPS) for guidance and control. However, GPS could not be used in several environments, for example, GPS has huge error near buildings and trees, indoor, and so on. In such GPS-denied environment, Laser Detection and Ranging (LIDER) sensor based navigation system have generally been used. However, LIDER sensor also has an weakness, and it could not be used in the open outdoor environment where GPS could be used. Therefore, it is desired to develop the integrated navigation system which is seamlessly applied to GPS and GPS-denied environments. In this paper, the integrated navigation system for aerial robot using GPS and LIDER is developed. The navigation system is designed based on Extended Kalman Filter, and the effectiveness of the developed system is verified by numerical simulation and experiment.
机译:在本研究中,提出了用于GPS和GPS拒绝环境中的空中机器人的新型鲁棒导航系统。通常,空中机器人使用来自全球定位系统(GPS)的位置和速度信息以进行引导和控制。但是,GPS无法在若干环境中使用,例如,GPS在建筑物和树木,室内等附近有巨大的错误。在这种GPS拒绝的环境中,通常使用基于激光检测和测距(林)传感器的导航系统。然而,林传感器也具有弱点,它不能用于可以使用GPS的开放式室外环境中使用。因此,希望开发集成导航系统,该系统无缝地应用于GPS和GPS拒绝环境。在本文中,开发了使用GPS和林德的空中机器人的集成导航系统。导航系统是基于扩展的卡尔曼滤波器设计的,并且通过数值模拟和实验验证了开发系统的有效性。

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