一个基于HOG的优化实时定性视觉伺服系统,用于自主轮椅
1Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, Al-Ahsa, Saudi Arabia. aabdulhafiz@kfu.edu.sa.
Scientific reports
|February 24, 2026
概括
本研究介绍了自主轮椅的更快,更有效的视觉伺服方法,改善了低功耗设备的实时导航. 基于定向梯度 (HOG) 的定性直方图 (QHOGVS) 提高了辅助移动系统的速度和稳定性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 计算机视觉 计算机视觉
- 辅助技术 辅助技术 辅助技术
背景情况:
- 实时性能对于自主移动系统至关重要.
- 现有的视觉伺服方法经常在低功耗硬件上的计算需求方面扎.
- 辅助移动需要可靠和精确的导航.
研究的目的:
- 为自主轮椅导航提供基于定向梯度 (HOG) 的视觉伺服 (QHOGVS) 方法的计算有效的直方图.
- 在保持导航精度的同时,在低功耗硬件上实现实时性能.
- 解决嵌入式系统中计算效率和导航精度之间的权衡问题.
主要方法:
- 开发了一种基于定向梯度 (HOG) 的视觉伺服 (QHOGVS) 算法的定性直方图.
- 使用 Python 矢量化优化了视觉服务管道.
- 包含一个自适应激活功能来调节错误的收.
主要成果:
- 在Raspberry Pi上实现了68倍的速度改进 (0.08 FPS到5.5 FPS).
- 在导航过程中证明了稳定的轨迹跟踪.
- 通过现实任务验证了系统在物理轮椅平台上的功能.
结论:
- 在低功耗嵌入式系统上,QHOGVS方法可实现实时自主轮椅导航.
- 该方法成功地平衡了计算效率和导航精度.
- 这项工作为实际的辅助技术提供了可行的解决方案,并为适应性视觉导航研究开辟了道路.
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