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Updated: Jun 7, 2025

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Published on: August 8, 2011

在室内环境中用于人机交互的基于FPGA的自适应加速器.

Mangali Sravanthi^1,2, Sravan Kumar Gunturi¹, Mangali Chinna Chinnaiah^3,4

¹Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Aziznagar, Hyderabad 500075, Telangana, India.

Sensors (Basel, Switzerland)

|November 9, 2024

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这项研究使用自适应现场可编程门阵列 (FPGA) 加速器来增强人机交互,用于实时室内定位和服务交付. 该系统准确地预测人类的姿势和机器人的意图,改善了狭窄空间的导航.

科学领域:

机器人技术机器人技术机器人技术
人工智能的人工智能
计算机工程计算机工程

背景情况:

在实时室内环境中的人机交互 (HRI) 对服务机器人提出了挑战,特别是在预测人类姿势和位置方面.
精确的人类定位和了解机器人的意图对于在狭窄的空间中无地提供服务至关重要.

研究的目的:

开发一种基于FPGA的适应性系统,用于室内环境中的实时人类定位和机器人意图估计.
增强服务机器人的人机隐式通信和导航能力.

主要方法:

利用与PIR和超声波传感器的传感器融合,用于静态和自适应人体姿势的二元分类.
为机器人任务交付和导航实施了自适应的同时定位和映射 (SLAM).
开发了用于算法实现和FPGA合成的VLSI硬件方案和Verilog HDL.

主要成果:

通过传感器融合成功演示了实时人类姿势分析和定位.
验证了基于SLAM的自适应三角导航方法,用于机器人服务交付.
在医院环境中使用基于Zed板的FPGAXilinx板进行实验验证.

结论:

关键词:

在FPGA中,FPGA是指FPGA.在本地化,本地化.姿势识别功能姿势识别功能融合传感器融合传感器融合传感器服务机器人服务机器人

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拟议的FPGA加速方法有效地解决了HRI中的实时人类本地化和机器人意图预测挑战.

开发的方法使得服务机器人在复杂的室内环境中能够进行自适应导航和隐式通信.

该系统的性能在现实的医院环境中得到了验证,展示了其实际适用性.