中文版 | English
题名

基于人机交互力的“半人马”负重行走助力系统研究

姓名
姓名拼音
YANG Ping
学号
12032731
学位类型
硕士
学位专业
0801Z1 智能制造与机器人
学科门类/专业学位类别
学术型::08 工学
导师
付成龙
导师单位
机械与能源工程系
论文答辩日期
2023-05-19
论文提交日期
2023-06-28
学位授予单位
南方科技大学
学位授予地点
深圳
摘要

负重行走是日常生活、抗灾救援、军事作战中的一项常见任务,长期负重可能 对人体造成不可逆的损伤。为辅助负重行走,研究人员提出了弹性背包、外骨骼 和外肢体等穿戴式助力装置。通过穿戴式机器人增强人体负重能力可以更大程度 发挥人体多地形适应、智能决策的优势。但现有的助力装置在负载支撑能力、人 机协同方面仍存在诸多不足。为满足穿戴式助力装置人机相融和负重助力的需求, 本文提出了一种新型人机协作负重的穿戴式机器人——“半人马”,并开展了样机 结构与硬件系统设计、协同负重行走交互力探索和基于人机交互力的协同柔顺控 制策略等关键技术的研究。

受四足生物负重运输能力和环境适应优势的生物启发,设计了双足引导、四 足负重的半人马式穿戴机器人。将机械腿后置于人体,既通过机械结构传递负载 重量、减轻人体负载压力,还可以避免机器人对人体行走运动的干扰。机器人足端 与人体双足构成的四足支撑多边形结构可在负重行走中为人机系统提供稳定支撑。 通过构建力矩与结构尺寸的约束方程,完成了对“半人马”机构关键尺寸参数的 求解。“半人马”机构与传感系统的搭建,为研究基于人机交互力的柔顺控制策略 提供稳定可靠的平台。

由于“半人马”是一种新型穿戴式负重助力机器人,可用于指导其为人体助 力的人机交互力规律尚未明晰。为此,设计了双人协同负重行走模式以模拟人体 穿戴“半人马”负重行走的运动机理。根据人体行走步态事件特征,构建了基于 足端 IMU 运动信息的步态划分策略。基于步态信息对交互力归一化处理,分析双 人协作负重行走中交互力的时空规律,并用于指导“半人马”的交互力运动控制。 通过心肺呼吸实验验证了协同行走能够减少人体新陈代谢消耗速率。

为实现人机协作负重行走,提出了一种基于人机交互力的柔顺控制策略。“半 人马”作为人机异构系统需要感知人体运动意图和物理交互信息,以实现高效的 人机协同负重。通过躯干姿态角与人机交互力的数据融合,实现了“半人马”系统 位姿平衡控制,以及与人体协同负重行走的柔顺交互控制。设计了负重行走对比 实验,验证了穿戴“半人马”机器人能够减少人体的足底压力。

关键词
语种
中文
培养类别
独立培养
入学年份
2020
学位授予年份
2023-06
参考文献列表

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