[1] 黄思翰,王柏村,张美迪,等.面向人本智造的新一代操作工:参考架构、使能技术与典型场景[J].机械工程学报,2022,58(18):251-264.HUANG Sihan,WANG Baicun,ZHANG Meidi,et al.Operator 4.0 towards human-centric smart manufacturing:Framework,enabling technologies and typical scenarios[J]. Journal of Mechanical Engineering,2022,58(18):251-264. [2] KAGIROV I,KAPUSTIN A,KIPYATKOVA I,et al.Medical exoskeleton "Remotion" with an intelligent control system:Modeling,implementation,and testing[J].Simulation Modelling Practice and Theory,2021,107:102200. [3] ZHANG X,CHEN X,HUO B,et al. An integrated evaluation approach of wearable lower limb exoskeletons for human performance augmentation[J]. Scientific Reports,2023,13(1):4251. [4] YAO Y M, SHAO D Q, TARABINI M, et al.Advancements in sensor technologies and control strategies for lower-limb rehabilitation exoskeletons:A comprehensive review[J]. Micromachines,2024,15(4):489. [5] MEHR J K,SHARIFI M,MUSHAHWAR V K,et al.Intelligent locomotion planning with enhanced postural stability for lower-limb exoskeletons[J]. IEEE Robotics and Automation Letters,2021,6(4):7588-7595. [6] LIAO H P,CHAN H H,LIU G Y,et al. Design,control and validation of a novel cabledriven series elastic actuation system for a flexible and portable back-support exoskeleton[J]. IEEE Transactions on Robotics,2024,40:2769-2790. [7] XING X Y,ZHANG S N,HUANG T H,et al. Spatial iterative learning torque control of robotic exoskeletons for high accuracy and rapid convergence assistance[J].IEEE/ASME Transactions on Mechatronics,2024,29(6):4215-4227. [8] WANG C,GUO Z M,DUAN S C,et al. A real-time stability control method through sEMG interface for lower extremity rehabilitation exoskeletons[J]. Frontiers in Neuroscience,2021,15:645374. [9] WANG J Q,WU D M,GAO Y Z,et al. Integral real-time locomotion mode recognition based on GA-CNN for lower limb exoskeleton[J]. Journal of Bionic Engineering,2022,19(5):1359-1373. [10] ZHEN T, YAN L. Real-time control strategy of exoskeleton locomotion trajectory based on multi-modal fusion[J]. Journal of Bionic Engineering,2023,20(6):2670-2682. [11] SALAMUN K,PAVI I,DAPO H,et al. Weakly hard real-time model for control systems:A survey[J].Sensors (Basel,Switzerland),2023,23(10):4652. [12] HE L, FAN W, DAI Z, et al. A human-machineenvironment interactive measurement system for non-anthropomorphic exoskeletons[J]. IEEE Transactions on Instrumentation and Measurement,2023,73:1-11. [13] WU X Y,LI J K,LIU L,et al. The visual footsteps planning system for exoskeleton robots under complex terrain[J]. IEEE Transactions on Systems, Man, and Cybernetics:Systems,2023,53(8):5149-5160. [14] WANG J,LIU J H,ZHANG G W,et al. Periodic event-triggered sliding mode control for lower limb exoskeleton based on human-robot cooperation[J]. ISA Transactions,2022,123:87-97. [15] KAWAMOTO H,LEE S,KANBE S,et al. Power assist method for HAL-3 using EMG-based feedback controller[C]//SMC'03 Conference Proceedings. 2003IEEE International Conference on Systems,Man and Cybernetics. Conference Theme-System Security and Assurance (Cat. No. 03CH37483). IEEE,2003,2:1648-1653. [16] SU B B, SMITH C, FAREWIK E G. Gait phase recognition using deep convolutional neural network with inertial measurement units[J]. Biosensors,2020,10(9):109. [17] PARK K W,CHOI J,KONG K. Data-driven modeling for gait phase recognition in a wearable exoskeleton using estimated forces[J]. IEEE Transactions on Robotics,2023,39(4):3072-3086. [18] WU X Y,YUAN Y,ZHANG X K,et al. Gait phase classification for a lower limb exoskeleton system based on a graph convolutional network model[J]. IEEE Transactions on Industrial Electronics,2021,69(5):4999-5008. [19] WEI H C,TONG R K,WANG M Y,et al. Gait phase detection based on LSTM-CRF for stair ambulation[J]. IEEE Robotics and Automation Letters,2023,8(9):6029-6035. [20] KANG I,MOLINARO D D,DUGGAL S,et al. Real-time gait phase estimation for robotic hip exoskeleton control during multimodal locomotion[J]. IEEE Robotics and Automation Letters,2021,6(2):3491-3497. [21] ZHANG Z W,CAI X F,ZHANG M B,et al. Real-time gait intention recognition for active control of unilateral knee exoskeleton[J]. Applied Bionics and Biomechanics,2024,2024(1):9426782. [22] CAO W J,MA Y,CHEN C J,et al. Hardware circuits design and performance evaluation of a soft lower limb exoskeleton[J]. IEEE Transactions on Biomedical Circuits and Systems,2022,16(3):384-394. [23] LI W,SHI P,LI S J,et al. Current status and clinical perspectives of extended reality for myoelectric prostheses[J]. Frontiers in Bioengineering and Biotechnology,2024,11:1334771. [24] JUN K,AKIRA K,SHOGO A,et al. Adaptive task scheduling for an assembly task coworker robot based on incremental learning of human's motion patterns[J]. IEEE Robotics and Automation Letters,2017,2(2):856-863. [25] LEE W K, JUNG S. FPGA design for controlling humanoid robot arms by exoskeleton motion capture system[C]//2006 IEEE International Conference on Robotics and Biomimetics. IEEE,2006:1378-1383. [26] SUN M W,OUYANG X P,MATTILA J,et al. One novel hydraulic actuating system for the lower-body exoskeleton[J]. Chinese Journal of Mechanical Engineering,2021,34(1):31. [27] SHETTY P R, MENEZES J A, SONG S. Ankle exoskeleton control via data-driven gait estimation for walking,running,and inclines[J]. IEEE Robotics and Automation Letters,2025,10(6):5855-5862. [28] LUO R M,SUN S Q,ZHANG X F,et al. A low-cost end-to-end s EMG-based gait sub-phase recognition system[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering,2019,28(1):267-276. [29] LIU Jia,BJORKMAN A,ANTFOLK C,et al. The Impact of stimulation parameters on reaction times following transcutaneous electrical stimulation in the lower leg[J].IEEE Transactions on Haptics,2025:1-11. [30] KIM J,LEE G,HEIMGARTNER R,et al. Reducing the metabolic rate of walking and running with a versatile,portable exosuit[J]. Science,2019,365(6454):668-672. [31] HAUFE F L,DUROYON E G,WOLF P,et al. Outside testing of wearable robots for gait assistance shows a higher metabolic benefit than testing on treadmills[J].Scientific Reports,2021,11(1):14833. |