基于数据融合的模拟低重力步态识别方法
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摘要
针对有动力航天服在进行主动助力时对人机系统下肢行走状态感知的需求,提出了基于数据融合的步态识别方法。首先设计了同步多源传感采集方案,分析了模拟低重力下的运动特点;将多源传感信息进行数据融合,针对不同运动模态和行走步态提取特征,基于模糊有限状态机进行步态相位划分。最后,在搭建的模拟低重力试验系统进行了运动测试验证,实测验证了本方法适用于平地行走和上下台阶等不同运动模式,获得了较高的识别准确率。
To meet the requirements of state perception of the lower limbs when actively assisted by powered spacesuit, a gait recognition method based on data fusion was proposed. The scheme of asynchronous multi-source sensor acquisition was designed and the characteristics of locomotion under simulated low gravity were analyzed. Then the data were fused, the features of different locomotion modes and walking gaits were extracted, and phases of gaits were classified by the Fuzzy Finite State Machine. In the end, the method was verified by experiments in the simulated low-gravity test system. The results demonstrated that the proposed method was suitable for gait recognition of different motion modes including walking, upstairs and downstairs, and a fairly high accuracy was reached.
To meet the requirements of state perception of the lower limbs when actively assisted by powered spacesuit, a gait recognition method based on data fusion was proposed. The scheme of asynchronous multi-source sensor acquisition was designed and the characteristics of locomotion under simulated low gravity were analyzed. Then the data were fused, the features of different locomotion modes and walking gaits were extracted, and phases of gaits were classified by the Fuzzy Finite State Machine. In the end, the method was verified by experiments in the simulated low-gravity test system. The results demonstrated that the proposed method was suitable for gait recognition of different motion modes including walking, upstairs and downstairs, and a fairly high accuracy was reached.
引文
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[2] Mcgee J, Carr C E. The Apollo number: space suits, self-support, and the walk-run [J]. Public Library of Science, 2009, 4(8):1-7.
[3] 周前祥. 舱外航天服的工效学问题及其研究方法[J].上海航天, 2005, 22(3): 47-51.Zhou Q.The work efficiency of spacesuit for EVA and its research way [J].Aerospace Shanghai, 2005, 22(3): 47-51.(in Chinese)
[4] Schiele A, Visent G. The ESA human arm exoskeleton for space robotics telepresence [C]//7th International Symposiumon Artificial Intelligence, Robotics and Automation in Space,Nara, Japan, 2003: 19-23.
[5] David Szondy. NASA developing exoskeleton for astronauts and the earthbound [N/OL]. US: Space,http://www.gizmag.com/x1-exoskeleton /24525/,2012-10-13.
[6] 郭庆, 张向刚, 秦开宇. 主动航天服下肢关节电动伺服控制机构研究[J]. 载人航天,2013, 19(5):75-79.Guo Q, Zhang X, Qin K. Research on electric servo control mechanism of lower extremity joint in active spacesuit[J].Manned Spaceflight, 2013 19(5): 75-79.(in Chinese)
[7] 张向刚,秦开宇,张羿,等. 基于外骨骼技术的舱外作业下肢运动能力增强技术[J]. 载人航天,2015,21(4):418-424.Zhang X, Qin K, Zhang Y,et al. A technology based on human exoskeleton for enhancing locomotion capability of lower extremity during extravehicular tasks[J]. Manned Spaceflight, 2015,21(4):418-424.(in Chinese)
[8] Syloslabini F, Lacquaniti F, Ivanenko Y P.Human locomotion underreduced gravity conditions: biomechanical and neurophysiological considerations [J]. Biomed Research International, 2014(23):547242.
[9] Donelan J M, Rodger K. Exploring dynamic similarity in human running using simulated reduced gravity[J]. J ExpBiol, 2000, 203: 2405-2415.
[10] 夏永明,赵自强,谈诚,等.不同重力环境下足底受力的步态差异分析[J].中国康复医学杂志,2013,28(3):215-219.Xia Y, Zhao Z, Tan C, et al.Difference of plantar force parameters in gait analysis between simulated zero-gravity and normal gravity locomotion[J]. Chinese Journal of Rehabilitation Medicine, 2013, 28(3): 215-219.(in Chinese)
[11] 谈诚,夏永明,曹毅,等.模拟不同重力环境下步态运动的足底受力分析[J].医用生物力学,2014,29(3):200-205.Tan C, Xia Y, Cao Y, et al. Gait analysis on plantar force under different simulated gravities[J]. Journal of Medical Biomechanics, 2014, 29(3):200-205.(in Chinese)
[12] Mc Crory J L, Derr J, Cavanagh P R. Locomotion in simulated zero gravity: ground reaction forces[J]. Aviat Space Environ Med, 2004, 75(3):203-210.
[13] De Witt J K, Perusek G P, Lewandowski B E, et al. Locomotion in simulated and real microgravity: horizontal suspension vs.parabolicflight[J]. Aviat Space Environ Med, 2010, 81(12):1092-1099.
[14] 滕召胜,罗隆福,童调生.智能检测系统与数据融合[M].北京:机械工业出版社,2000: 202-203.Teng Z, Luo L, Tong D. Intelligent Detection System and Data Fusion[M]. Beijing:China Machine Press, 2000: 202-203.(in Chinese)
[15] Chang Y H, Huang H W, Hamerski C M, et al. The independent effects of gravity and inertia on running mechanics[J]. Journal of Experimental Biology, 2000, 203(2):229-238.
[16] 周洁. 基于姿态与压力信息的步态识别方法[D].成都:西南交通大学,2016.Zhou J. Gait Recognition Method Based on Attitude and Pressure Information[D]. Chengdu: Southwest Jiaotong University, 2016.(in Chinese)
[17] 柴虎.下肢外骨骼机器人跟随系统的研究[D]. 广州:南方医科大学,2013.Chai H. The Study on Servo System for the Lower Extremity Exoskeleton Robot[D]. Guangzhou: Southern Medical University, 2013.(in Chinese)