螺旋桨驱动混合UGV稳定与控制的鲁棒人工智能方法

Bushra Rasheed, M. Usama, Asmara Safdar
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引用次数: 0

摘要

混合动力无人地面飞行器(HUGV)利用螺旋桨的多向推力,可以在包括墙壁在内的任何地形上行驶和飞行。在工业革命时代,混合动力ugv需要具备自主性和智能决策能力。在混合动力ugv爬壁过程中,稳定性是至关重要的,它依赖于多个传感器的实时反馈。为了提高稳定性和控制性,建议用基于AI的算法取代PID控制回路,以减少决策时间和数学复杂度。对于任意地形的自主运动,智能ugv可以同时进行地图和定位。他们可以通过使用实时传感器读数做出关于运动模式的智能决策,即在地面或墙壁上驾驶,在地面或墙壁上转向,飞行和机动。所提出的人工智能模型与HUGV的集成可以应用于许多人类难以进入的领域,例如;大型结构检测、生物和核危害环境检测、行星探测和磁场检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Artificial Intelligence Approach to Stabilize and Control Propeller Driven Hybrid UGV
Hybrid Unmanned Ground Vehicle (HUGV) can drive on any terrain including walls and fly as well, using the multi directional thrust force of propellers. In the era of industrial revolution, hybrid UGVs need to be autonomous with intelligent decision making capabilities. During wall climbing of hybrid UGVs, stability is essential and depends on real time feedback from multiple sensors. To increase stability and control, it is proposed that PID control loops should be replaced by AI based algorithms that reduce the decision time and mathematical complexity. For autonomous movement in any terrain using the proposed model, intelligent UGVs can map and localize simultaneously.They can make intelligent decisions about mode of movement i.e. driving on ground or wall, steering on ground or wall, flying and maneuvering by using real time sensor readings. Integration of the proposed AI models with HUGV can be applied to many areas which are hard for humans to access, for instance; inspection of large structures, bio & nuclear hazard environments, planetary exploration & magnetic fields detection.
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