基于深度学习算法的智能电动轮椅减震系统设计

Design of Intelligent Electric Wheelchair Shock Absorption System Based on Deep Learning Algorithm

  • 摘要: 针对老年人与残疾人出行中轮椅减震舒适性不足的问题,本文提出轻量化快速响应主动悬架系统(LARSS)。系统集成激光雷达与双目摄像头获取环境信息,借助深度学习技术体系中的3D-CNN和向量嵌入算法处理数据,构建地面高度云点图,结合模糊PID算法解析路面特征,驱动主动悬架实现毫秒级动态响应。实践表明,该系统有效强化复杂路况下的减震效能,达成环境感知、数据处理与悬架控制的高效联动,为特殊群体营造稳定舒适的出行条件,具备显著的工程应用潜力。

     

    Abstract: Aiming at the problem of insufficient shock absorption comfort of wheelchairs during the travel of the elderly and disabled, this paper proposed a lightweight and fast - response active suspension system (LARSS). The system integrated LiDAR and binocular cameras to obtain environmental information, used 3D - CNN and vector embedding algorithms in the deep - learning technology system to process data, constructed a ground height cloud point map, analyzed road surface features with the fuzzy PID algorithm, and drived the active suspension to achieve millisecond - level dynamic response. Practice showed that this system effectively enhanced the shock absorption performance under complex road conditions, realized the efficient linkage of environmental perception, data processing, and suspension control, created stable and comfortable travel conditions for special groups, and had significant engineering application potential.

     

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