Similar articles

Abstract: Today, exoskeletons are widely applied to provide walking assistance for patients with lower limb motor incapacity. Most existing exoskeletons are under-actuated, resulting in a series of problems, e.g., interference and unnatural gait during walking. In this study, we propose a novel intelligent autonomous lower extremity exoskeleton (Auto-LEE), aiming at improving the user experience of wearable walking aids and extending their application range. Unlike traditional exoskeletons, Auto-LEE has 10 degrees of freedom, and all the joints are actuated independently by direct current motors, which allows the robot to maintain balance in aiding walking without extra support. The new exoskeleton is designed and developed with a modular structure concept and multi-modal human-robot interfaces are considered in the control system. To validate the ability of self-balancing bipedal walking, three general algorithms for generating walking patterns are researched, and a preliminary experiment is implemented.

一种新型自主下肢外骨骼助行机器人的研制

[1]Brown-Triolo DL, Roach MJ, Nelson K, et al., 2002. Consumer perspectives on mobility: implications for neuroprosthesis design. J Rehabil Res Dev, 39(6):659-669.

[2]Cenciarini M, Dollar AM, 2011. Biomechanical considerations in the design of lower limb exoskeletons. IEEE Int Conf on Rehabilitation Robotics, p.1-6.

[3]Fang Y, Yu Y, Chen F, et al., 2008. Dynamic analysis and control strategy of the wearable power assist leg. IEEE Int Conf on Automation and Logistics, p.1060-1065.

[4]Gao S, 2004. Practical Anatomical Atlas: Lower Limbs Volume. Shanghai Science and Technology Press, Shanghai (in Chinese).

[5]Gardner AD, Potgieter J, Noble FK, 2017. A review of commercially available exoskeletons’capabilities. 24^th Int Conf on Mechatronics and Machine Vision in Practice, p.1-5.

[6]Kajita S, Kanehiro F, Kaneko K, et al., 2001. The 3D linear inverted pendulum mode: a simple modeling for a biped walking pattern generation. IEEE/RSJ Int Conf on Intelligent Robots and Systems, p.239-246.

[7]Kajita S, Kanehiro F, Kaneko K, et al., 2003. Biped walking pattern generation by using preview control of zero-moment point. IEEE Int Conf on Robotics and Automation, p.1620-1626.

[8]Katayama T, Ohki T, Inoue T, et al., 1985. Design of an optimal controller for a discrete-time system subject to previewable demand. Int J Contr, 41(3):677-699.

[9]Kong K, Jeon D, 2006. Design and control of an exoskeleton for the elderly and patients. IEEE/ASME Trans Mech, 11(4):428-432.

[10]Kong K, Moon H, Hwang B, et al., 2009. Impedance compensation of SUBAR for back-drivable force-mode actuation. IEEE Trans Rob, 25(3):512-521.

[11]Kopp C, 2011. Exoskeletons for warriors of the future. Defence Today, 9(2):38-40.

[12]McDonald JW, Sadowsky C, 2002. Spinal-cord injury. Lancet, 359(9304):417-425.

[13]Mertz L, 2012. The next generation of exoskeletons: lighter, cheaper devices are in the works. IEEE Pulse, 3(4):56-61.

[14]Mori Y, Taniguchi T, Inoue K, et al., 2011. Development of a standing style transfer system able with novel crutches for a person with disabled lower limbs. J Syst Des Dyn, 5(1):83-93.

[15]National Spinal Cord Injury Statistical Center, 2016. Spinal Cord Injury Facts and Figures at a Glance. https://www.nscisc.uab.edu/Public/Facts

[16]Protection B, Labour M, 1988. Human Dimensions of Chinese Adults, GB 10000-1988. National Standards of People’s Republic of China (in Chinese).

[17]Shimmyo S, Sato T, Ohnishi K, 2013. Biped walking pattern generation by using preview control based on three-mass model. IEEE Trans Ind Electron, 60(11):5137-5147.

[18]Strausser KA, Swift TA, Zoss AB, et al., 2010. Prototype medical exoskeleton for paraplegic mobility: first experimental results. ASME Dynamic Systems and Control Conf, p.453-458.

[19]Talaty M, Esquenazi A, Brice no JE, 2013. Differentiating ability in users of the rewalk^TM powered exoskeleton: an analysis of walking kinematics. IEEE Int Conf on Rehabilitation Robotics, p.1-5.

[20]Tsukahara A, Hasegawa Y, Eguchi K, et al., 2015. Restoration of gait for spinal cord injury patients using HAL with intention estimator for preferable swing speed. IEEE Trans Neur Syst Rehab Eng, 23(2):308-318.

[21]Vukobratović M, Borovac B, 2004. Zero-moment point—thirty five years of its life. Int J Humanoid Rob, 1(1):157-173.

[22]Zhang SM, Wang C, Wu XY, et al., 2016. Real time gait planning for a mobile medical exoskeleton with crutche. IEEE Int Conf on Robotics and Biomimetics, p.2301-2306.

[23]Zoss AB, Kazerooni H, Chu A, 2006. Biomechanical design of the Berkeley lower extremity exoskeleton (BLEEX). IEEE/ASME Trans Mech, 11(2):128-138.