Статті в журналах: "Human-exoskeleton interaction"

1

Moreno, Juan C., Fernando Brunetti, Enrique Navarro, Arturo Forner-Cordero, and José L. Pons. "Analysis of the Human Interaction with a Wearable Lower-Limb Exoskeleton." Applied Bionics and Biomechanics 6, no. 2 (2009): 245–56. http://dx.doi.org/10.1155/2009/712530.

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The design of a wearable robotic exoskeleton needs to consider the interaction, either physical or cognitive, between the human user and the robotic device. This paper presents a method to analyse the interaction between the human user and a unilateral, wearable lower-limb exoskeleton. The lower-limb exoskeleton function was to compensate for muscle weakness around the knee joint. It is shown that the cognitive interaction is bidirectional; on the one hand, the robot gathered information from the sensors in order to detect human actions, such as the gait phases, but the subjects also modified their gait patterns to obtain the desired responses from the exoskeleton. The results of the two-phase evaluation of learning with healthy subjects and experiments with a patient case are presented, regarding the analysis of the interaction, assessed in terms of kinematics, kinetics and/or muscle recruitment. Human-driven response of the exoskeleton after training revealed the improvements in the use of the device, while particular modifications of motion patterns were observed in healthy subjects. Also, endurance (mechanical) tests provided criteria to perform experiments with one post-polio patient. The results with the post-polio patient demonstrate the feasibility of providing gait compensation by means of the presented wearable exoskeleton, designed with a testing procedure that involves the human users to assess the human-robot interaction.

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2

Wang, Zhipeng, Chifu Yang, Zhen Ding, Tao Yang, Hao Guo, Feng Jiang, and Bowen Tian. "Study on the Control Method of Knee Joint Human–Exoskeleton Interactive System." Sensors 22, no. 3 (January 28, 2022): 1040. http://dx.doi.org/10.3390/s22031040.

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The advantages of exoskeletons based on the Bowden cable include being lightweight and flexible, thus being convenient in assisting humans. However, the performance of an exoskeleton is limited by the structure and human–exoskeleton interaction, which is analyzed from the established mathematical model of the human–exoskeleton system. In order to improve the auxiliary accuracy, corresponding control methods are proposed. The disturbance observer is designed to compensate for disturbances and parameter perturbations in the inner loop. The human–exoskeleton interaction feedforward model is integrated into the admittance control, which overcomes the limitation of the force loading caused by the friction of the Bowden cable and the change in stiffness of the human–exoskeleton interaction. Furthermore, an angle prediction method using the encoder as the signal source is designed to reduce the disturbance of the force loading caused by human motion. Finally, the effectiveness of the design method proposed in this paper is verified through experiments.

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3

Wang, Xin, Qiuzhi Song, Shitong Zhou, Jing Tang, Kezhong Chen, and Heng Cao. "Multi-connection load compensation and load information calculation for an upper-limb exoskeleton based on a six-axis force/torque sensor." International Journal of Advanced Robotic Systems 16, no. 4 (July 2019): 172988141986318. http://dx.doi.org/10.1177/1729881419863186.

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In this article, a method of multi-connection load compensation and load information calculation for an upper-limb exoskeleton is proposed based on a six-axis force/torque sensor installed between the exoskeleton and the end effector. The proposed load compensation method uses a mounted sensor to measure the force and torque between the exoskeleton and load of different connections and adds a compensator to the controller to compensate the component caused by the load in the human–robot interaction force, so that the human–robot interaction force is only used to operate the exoskeleton. Therefore, the operator can manipulate the exoskeleton with the same interaction force to lift loads of different weights with a passive or fixed connection, and the human–robot interaction force is minimized. Moreover, the proposed load information calculation method can calculate the weight of the load and the position of its center of gravity relative to the exoskeleton and end effector accurately, which is necessary for acquiring the upper-limb exoskeleton center of gravity and stability control of whole-body exoskeleton. In order to verify the effectiveness of the proposed method, we performed load handling and operational stability experiments. The experimental results showed that the proposed method realized the expected function.

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4

Zhao, Zhirui, Xing Li, Mingfang Liu, Xingchen Li, Haoze Gao, and Lina Hao. "A novel human-robot interface based on soft skin sensor designed for the upper-limb exoskeleton." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 236, no. 1 (September 30, 2021): 566–78. http://dx.doi.org/10.1177/09544062211035801.

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The upper-limb exoskeleton is capable of enhancing human arm strength beyond normal levels, whereas deriving the operator’s desired action straightforward turns out to be one of the significant difficulties facing human-robot interaction research. In the study, the human-robot interface was presented to regulate the exoskeleton tracking human elbow motion trajectory that employed the contact force signals between the exoskeleton and its operator as the primary means of information transportation. The signals were recorded by adopting the novel soft skin sensors attached to the bracket on the exoskeleton linkage, which could reflect the human arm motion intention through the virtual admittance model and adaptive control. Subsequently, a 1-DOF upper-limb exoskeleton was designed to illustrate the performance of the proposed sensor and the interaction control method in the human-robot cooperation experiment.

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5

Xia, Kang, Xianglei Chen, Xuedong Chang, Chongshuai Liu, Liwei Guo, Xiaobin Xu, Fangrui Lv, Yimin Wang, Han Sun, and Jianfang Zhou. "Hand Exoskeleton Design and Human–Machine Interaction Strategies for Rehabilitation." Bioengineering 9, no. 11 (November 11, 2022): 682. http://dx.doi.org/10.3390/bioengineering9110682.

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Stroke and related complications such as hemiplegia and disability create huge burdens for human society in the 21st century, which leads to a great need for rehabilitation and daily life assistance. To address this issue, continuous efforts are devoted in human–machine interaction (HMI) technology, which aims to capture and recognize users’ intentions and fulfil their needs via physical response. Based on the physiological structure of the human hand, a dimension-adjustable linkage-driven hand exoskeleton with 10 active degrees of freedom (DoFs) and 3 passive DoFs is proposed in this study, which grants high-level synergy with the human hand. Considering the weight of the adopted linkage design, the hand exoskeleton can be mounted on the existing up-limb exoskeleton system, which greatly diminishes the burden for users. Three rehabilitation/daily life assistance modes are developed (namely, robot-in-charge, therapist-in-charge, and patient-in-charge modes) to meet specific personal needs. To realize HMI, a thin-film force sensor matrix and Inertial Measurement Units (IMUs) are installed in both the hand exoskeleton and the corresponding controller. Outstanding sensor–machine synergy is confirmed by trigger rate evaluation, Kernel Density Estimation (KDE), and a confusion matrix. To recognize user intention, a genetic algorithm (GA) is applied to search for the optimal hyperparameters of a 1D Convolutional Neural Network (CNN), and the average intention-recognition accuracy for the eight actions/gestures examined reaches 97.1% (based on K-fold cross-validation). The hand exoskeleton system provides the possibility for people with limited exercise ability to conduct self-rehabilitation and complex daily activities.

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6

Huang, Rui, Hong Cheng, Hongliang Guo, Xichuan Lin, and Jianwei Zhang. "Hierarchical learning control with physical human-exoskeleton interaction." Information Sciences 432 (March 2018): 584–95. http://dx.doi.org/10.1016/j.ins.2017.09.068.

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7

Ballen-Moreno, Felipe, Margarita Bautista, Thomas Provot, Maxime Bourgain, Carlos A. Cifuentes, and Marcela Múnera. "Development of a 3D Relative Motion Method for Human–Robot Interaction Assessment." Sensors 22, no. 6 (March 21, 2022): 2411. http://dx.doi.org/10.3390/s22062411.

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Exoskeletons have been assessed by qualitative and quantitative features known as performance indicators. Within these, the ergonomic indicators have been isolated, creating a lack of methodologies to analyze and assess physical interfaces. In this sense, this work presents a three-dimensional relative motion assessment method. This method quantifies the difference of orientation between the user’s limb and the exoskeleton link, providing a deeper understanding of the Human–Robot interaction. To this end, the AGoRA exoskeleton was configured in a resistive mode and assessed using an optoelectronic system. The interaction quantified a difference of orientation considerably at a maximum value of 41.1 degrees along the sagittal plane. It extended the understanding of the Human–Robot Interaction throughout the three principal human planes. Furthermore, the proposed method establishes a performance indicator of the physical interfaces of an exoskeleton.

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8

Ajayi, Michael Oluwatosin, Karim Djouani, and Yskandar Hamam. "Interaction Control for Human-Exoskeletons." Journal of Control Science and Engineering 2020 (June 26, 2020): 1–15. http://dx.doi.org/10.1155/2020/8472510.

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In this work, a general concept of the human-exoskeleton compatibility and interaction control is addressed. Rehabilitation, as applied to humans with motor control disorder, involves repetitive gait training in relation to lower limb extremity and repetitive task training in relation to upper limb extremity. It is in this regard that exoskeletal systems must be kinematically compatible with those of the subject in order to guarantee that the subject is being trained properly. The incompatibility between the wearable robotic device and the wearer results in joint misalignment, thus introducing interaction forces during movement. This, therefore, leads to the introduction of the need for interaction control in wearable robotic devices. Human-exoskeleton joint alignment is an uphill task; hence, measures to actualize this in order to guarantee the safety and comfort of humans are necessary. These measures depend on the types of joints involved in the rehabilitation or assistive process. Hence, several upper and lower extremity exoskeletons with concepts relating to interaction forces reduction are reviewed. The significant distinction in the modelling strategy of lower and upper limb exoskeletons is highlighted. Limitations of certain exoskeletal systems which may not allow the application of interaction control are also discussed.

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9

Massardi, Stefano, David Rodriguez-Cianca, David Pinto-Fernandez, Juan C. Moreno, Matteo Lancini, and Diego Torricelli. "Characterization and Evaluation of Human–Exoskeleton Interaction Dynamics: A Review." Sensors 22, no. 11 (May 25, 2022): 3993. http://dx.doi.org/10.3390/s22113993.

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Exoskeletons and exosuits have witnessed unprecedented growth in recent years, especially in the medical and industrial sectors. In order to be successfully integrated into the current society, these devices must comply with several commercialization rules and safety standards. Due to their intrinsic coupling with human limbs, one of the main challenges is to test and prove the quality of physical interaction with humans. However, the study of physical human–exoskeleton interactions (pHEI) has been poorly addressed in the literature. Understanding and identifying the technological ways to assess pHEI is necessary for the future acceptance and large-scale use of these devices. The harmonization of these evaluation processes represents a key factor in building a still missing accepted framework to inform human–device contact safety. In this review, we identify, analyze, and discuss the metrics, testing procedures, and measurement devices used to assess pHEI in the last ten years. Furthermore, we discuss the role of pHEI in safety contact evaluation. We found a very heterogeneous panorama in terms of sensors and testing methods, which are still far from considering realistic conditions and use-cases. We identified the main gaps and drawbacks of current approaches, pointing towards a number of promising research directions. This review aspires to help the wearable robotics community find agreements on interaction quality and safety assessment testing procedures.

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10

Yoon, Soocheol, Ya-Shian Li-Baboud, Ann Virts, Roger Bostelman, and Mili Shah. "Feasibility of using depth cameras for evaluating human - exoskeleton interaction." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (September 2022): 1892–96. http://dx.doi.org/10.1177/1071181322661190.

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With the increased use of exoskeletons in a variety of fields such as industry, military, and health care, there is a need for measurement standards to understand the effects of exoskeletons on human motion. Optical tracking systems (OTS) provide high accuracy human motion tracking, but are expensive, require markers, and constrain the tests to a specified area where the cameras can provide sufficient coverage. This study describes the feasibility of using lower cost, portable, markerless depth camera systems for measuring human and exoskeleton 3-dimensional (3D) joint positions and angles. A human performing a variety of industrial tasks while wearing three different exoskeletons was tracked by both an OTS with modified skeletal models and a depth camera body tracking system. A comparison of the acquired data was then used to facilitate discussions regarding the potential use of depth cameras for exoskeleton evaluation.

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11

Pinheiro, Cristiana, Joana Figueiredo, Nuno Magalhães, and Cristina P. Santos. "Wearable Biofeedback Improves Human-Robot Compliance during Ankle-Foot Exoskeleton-Assisted Gait Training: A Pre-Post Controlled Study in Healthy Participants." Sensors 20, no. 20 (October 17, 2020): 5876. http://dx.doi.org/10.3390/s20205876.

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The adjunctive use of biofeedback systems with exoskeletons may accelerate post-stroke gait rehabilitation. Wearable patient-oriented human-robot interaction-based biofeedback is proposed to improve patient-exoskeleton compliance regarding the interaction torque’s direction (joint motion strategy) and magnitude (user participation strategy) through auditory and vibrotactile cues during assisted gait training, respectively. Parallel physiotherapist-oriented strategies are also proposed such that physiotherapists can follow in real-time a patient’s motor performance towards effective involvement during training. A preliminary pre-post controlled study was conducted with eight healthy participants to conclude about the biofeedback’s efficacy during gait training driven by an ankle-foot exoskeleton and guided by a technical person. For the study group, performance related to the interaction torque’s direction increased during (p-value = 0.07) and after (p-value = 0.07) joint motion training. Further, the performance regarding the interaction torque’s magnitude significantly increased during (p-value = 0.03) and after (p-value = 68.59 × 10−3) user participation training. The experimental group and a technical person reported promising usability of the biofeedback and highlighted the importance of the timely cues from physiotherapist-oriented strategies. Less significant improvements in patient–exoskeleton compliance were observed in the control group. The overall findings suggest that the proposed biofeedback was able to improve the participant-exoskeleton compliance by enhancing human-robot interaction; thus, it may be a powerful tool to accelerate post-stroke ankle-foot deformity recovery.

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12

Athrey, Prajwal L. "Design and Fabrication of Exoskeleton Arm for Lifting Weight." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 4931–32. http://dx.doi.org/10.22214/ijraset.2022.45127.

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Abstract: For centuries now, humans have developed machines for tasks which are too labour intensive for species cannot do. So, creative imagination and subtle engineering has led to the development of the powered exoskeleton. It is a device which can be worn over the human body. The robotic exoskeleton systems are developed significantly to be used for human power assist and haptic interaction with human Motion. The designed pneumatic arm consists of cylinders, a shaft efforts with lead screw mechanism able of converting a movement of piston to rotational movement of arm by utilizing the compressed air from pneumatic system. The designed processes of the suit is carried out based on some integrated information of kinematic, dynamics and structural analysis of the desired exoskeleton configuration as a whole. Since, such exoskeleton directly interacts with a human body there are some mechanical limitations to its design. While designing such exoskeleton movable range of arms, safety and comfort Wearing, low inertia, adaptability are considered.

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13

Schiele, André, and Frans C. T. van der Helm. "Influence of Attachment Pressure and Kinematic Configuration on pHRI with Wearable Robots." Applied Bionics and Biomechanics 6, no. 2 (2009): 157–73. http://dx.doi.org/10.1155/2009/829219.

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The goal of this paper is to show the influence of exoskeleton attachment, such as the pressure on the fixation cuffs and alignment of the robot joint to the human joint, on subjective and objective performance metrics (i.e. comfort, mental load, interface forces, tracking error and available workspace) during a typical physical human-robot interaction (pHRI) experiment. A mathematical model of a single degree of freedom interaction between humans and a wearable robot is presented and used to explain the causes and characteristics of interface forces between the two. The pHRI model parameters (real joint offsets, attachment stiffness) are estimated from experimental interface force measurements acquired during tests with 14 subjects. Insights gained by the model allow optimisation of the exoskeleton kinematics. This paper shows that offsets of more than ±10 cm exist between human and robot axes of rotation, even if a well-designed exoskeleton is aligned properly before motion. Such offsets can create interface loads of up to 200 N and 1.5 Nm in the absence of actuation. The optimal attachment pressure is determined to be 20 mmHg and the attachment stiffness is about 300 N/m. Inclusion of passive compensation joints in the exoskeleton is shown to lower the interaction forces significantly, which enables a more ergonomic pHRI.

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14

Norhafizan, A., R. A. R. Ghazilla, Vijayabaskar Kasi, Z. Taha, and Bilal Hamid. "A Review on Lower-Limb Exoskeleton System for Sit to Stand, Ascending and Descending Staircase Motion." Applied Mechanics and Materials 541-542 (March 2014): 1150–55. http://dx.doi.org/10.4028/www.scientific.net/amm.541-542.1150.

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Robotic exoskeleton system has been found to be an active area of study which being used in human power augmentation, human power assistance, robotic rehabilitation, and haptic interaction in virtual reality developed in recent robotic research. In recent years, the application of robotic exoskeleton has become more prominent as to provide alternative solutions for physically less incapable people (PLIP) support in their daily movements. Most common difficulties faced by PLIP are in sit-to-stand, ascending and descending staircases. Unlike industrial robots, the robotic exoskeleton systems need to consider a special design because they directly interact with human user. In the mechanical design of these systems, human and robotic suitable kinematics, wearer safety, human user comfort wearing, low inertia, and adaptability should be especially considered. Controllability, responsiveness, flexible and smooth motion generation, and safety should especially be considered in the controllers of exoskeleton systems. Furthermore, the controller should generate the motions in accordance with the human motion intention. This paper briefly reviews the lower-limb robotic exoskeleton systems. In the short review, it is focused to identify the brief history, basic concept, challenges, and future development of the robotic exoskeleton systems to assist the physically less incapable people (PLIP) in rising up, sitting, ascending and descending staircases. Furthermore, key technologies of lower-limb exoskeleton systems are reviewed by taking state-of-the-art robot as examples. Keywords: List the Robotic exoskeleton systems, rehabilitation robotics, man-machine intelligent system

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15

Rabaseda, Alexandre, Emelie Seguin, and Marc Doumit. "Enhancing Human Mobility Exoskeleton Comfort Using Admittance Controller." WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE 18 (March 18, 2021): 24–31. http://dx.doi.org/10.37394/23208.2021.18.3.

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Human mobility exoskeletons have been in development for several years and are becoming increasingly efficient. Unfortunately, user comfort was not always a priority design criterion throughout their development. To further improve this technology, exoskeletons should operate and deliver assistance without causing discomfort to the user. For this, improvements are necessary from an ergonomic point of view. The device’s control method is important when endeavoring to enhance user comfort. Exoskeleton or rehabilitation device controllers use methods of control called interaction controls (admittance and impedance controls). This paper proposes an extended version of an admittance controller to enhance user comfort. The control method used consists of adding an inner loop that is controlled by a proportional-integral-derivative (PID) controller. This allows the interaction force to be kept as close as possible to the desired force trajectory. The force-tracking admittance controller modifies the actuation force of the system in order to follow both the desired motion trajectory and the desired relative force between the user and the exoskeleton.

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16

Kim, Y. S., J. Lee, S. Lee, and M. Kim. "A Force Reflected Exoskeleton-Type Masterarm for Human–Robot Interaction." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 35, no. 2 (March 2005): 198–212. http://dx.doi.org/10.1109/tsmca.2004.832836.

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17

Rodrigues-Carvalho, Camila, Marvin Fernández-García, David Pinto-Fernández, Clara Sanz-Morere, Filipe Oliveira Barroso, Susana Borromeo, Cristina Rodríguez-Sánchez, Juan C. Moreno, and Antonio J. del-Ama. "Benchmarking the Effects on Human–Exoskeleton Interaction of Trajectory, Admittance and EMG-Triggered Exoskeleton Movement Control." Sensors 23, no. 2 (January 10, 2023): 791. http://dx.doi.org/10.3390/s23020791.

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Nowadays, robotic technology for gait training is becoming a common tool in rehabilitation hospitals. However, its effectiveness is still controversial. Traditional control strategies do not adequately integrate human intention and interaction and little is known regarding the impact of exoskeleton control strategies on muscle coordination, physical effort, and user acceptance. In this article, we benchmarked three types of exoskeleton control strategies in a sample of seven healthy volunteers: trajectory assistance (TC), compliant assistance (AC), and compliant assistance with EMG-Onset stepping control (OC), which allows the user to decide when to take a step during the walking cycle. This exploratory study was conducted within the EUROBENCH project facility. Experimental procedures and data analysis were conducted following EUROBENCH’s protocols. Specifically, exoskeleton kinematics, muscle activation, heart and breathing rates, skin conductance, as well as user-perceived effort were analyzed. Our results show that the OC controller showed robust performance in detecting stepping intention even using a corrupt EMG acquisition channel. The AC and OC controllers resulted in similar kinematic alterations compared to the TC controller. Muscle synergies remained similar to the synergies found in the literature, although some changes in muscle contribution were found, as well as an overall increase in agonist-antagonist co-contraction. The OC condition led to the decreased mean duration of activation of synergies. These differences were not reflected in the overall physiological impact of walking or subjective perception. We conclude that, although the AC and OC walking conditions allowed the users to modulate their walking pattern, the application of these two controllers did not translate into significant changes in the overall physiological cost of walking nor the perceived experience of use. Nonetheless, results suggest that both AC and OC controllers are potentially interesting approaches that can be explored as gait rehabilitation tools. Furthermore, the INTENTION project is, to our knowledge, the first study to benchmark the effects on human–exoskeleton interaction of three different exoskeleton controllers, including a new EMG-based controller designed by us and never tested in previous studies, which has made it possible to provide valuable third-party feedback on the use of the EUROBENCH facility and testbed, enriching the apprenticeship of the project consortium and contributing to the scientific community.

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18

Jin, Xin, Jia Guo, Zhong Li, and Ruihao Wang. "Motion Prediction of Human Wearing Powered Exoskeleton." Mathematical Problems in Engineering 2020 (December 21, 2020): 1–8. http://dx.doi.org/10.1155/2020/8899880.

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With the development of powered exoskeleton in recent years, one important limitation is the capability of collaborating with human. Human-machine interaction requires the exoskeleton to accurately predict the human motion of the upcoming movement. Many recent works implement neural network algorithms such as recurrent neural networks (RNN) in motion prediction. However, they are still insufficient in efficiency and accuracy. In this paper, a Gaussian process latent variable model (GPLVM) is employed to transform the high-dimensional data into low-dimensional data. Combining with the nonlinear autoregressive (NAR) neural network, the GPLVM-NAR method is proposed to predict human motions. Experiments with volunteers wearing powered exoskeleton performing different types of motion are conducted. Results validate that the proposed method can forecast the future human motion with relative error of 2%∼5% and average calculation time of 120 s∼155 s, depending on the type of different motions.

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Fang, Qianqian, Tian Xu, Tianjiao Zheng, Hegao Cai, Jie Zhao, and Yanhe Zhu. "A Rehabilitation Training Interactive Method for Lower Limb Exoskeleton Robot." Mathematical Problems in Engineering 2022 (April 20, 2022): 1–15. http://dx.doi.org/10.1155/2022/2429832.

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Rehabilitation exoskeleton robot plays an important role in rehabilitation training for limb-disabled patients and exoskeleton robots are becoming popular in rehabilitation area. To encourage the patient's active participation, the patient's subjective motion intention needs to be considered. In this paper, a rehabilitation training interactive method of lower limb exoskeleton robot based on patient's intention is proposed. The proposed method benefits patients to adjust the training trajectory in a safe range of motion according to their intentions. That is, the patient can adjust the amplitude of the trajectory and even the initial point of the trajectory by applying external interaction force to the human-robot system. To identify the patient's intention, the classical momentum observer is introduced to detect the interaction force between the patient and the exoskeleton. In addition, joint space trajectories and Cartesian space trajectories with different amplitudes are designed to enrich the training contents. Then, a trajectory switching algorithm based on external interaction recognition and designed training trajectories is developed. Finally, the proposed method is supported by the simulation results on a lower limb exoskeleton with 2 degrees of freedom (DoF).

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20

Wang, Sun’an, Binquan Zhang, Zhenyuan Yu, and Yu’ang Yan. "Differential Soft Sensor-Based Measurement of Interactive Force and Assistive Torque for a Robotic Hip Exoskeleton." Sensors 21, no. 19 (September 30, 2021): 6545. http://dx.doi.org/10.3390/s21196545.

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With the emerging of wearable robots, the safety and effectiveness of human-robot physical interaction have attracted extensive attention. Recent studies suggest that online measurement of the interaction force between the robot and the human body is essential to the aspects above in wearable exoskeletons. However, a large proportion of existing wearable exoskeletons monitor and sense the delivered force and torque through an indirect-measure method, in which the torque is estimated by the motor current. Direct force/torque measuring through low-cost and compact wearable sensors remains an open problem. This paper presents a compact soft sensor system for wearable gait assistance exoskeletons. The contact force is converted into a voltage signal by measuring the air pressure within a soft pneumatic chamber. The developed soft force sensor system was implemented on a robotic hip exoskeleton, and the real-time interaction force between the human thigh and the exoskeleton was measured through two differential soft chambers. The delivered torque of the hip exoskeleton was calculated based on a characterization model. Experimental results suggested that the sensor system achieved direct force measurement with an error of 10.3 ± 6.58%, and torque monitoring for a hip exoskeleton which provided an understanding for the importance of direct force/torque measurement for assistive performance. Compared with traditional rigid force sensors, the proposed system has several merits, as it is compact, low-cost, and has good adaptability to the human body due to the soft structure.

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21

Chakarov, D., I. Veneva, M. Tsveov, and T. Tiankov. "New Exoskeleton Arm Concept Design And Actuation For Haptic Interaction With Virtual Objects." Journal of Theoretical and Applied Mechanics 44, no. 4 (December 1, 2014): 3–14. http://dx.doi.org/10.2478/jtam-2014-0019.

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Abstract In the work presented in this paper the conceptual design and actuation of one new exoskeleton of the upper limb is presented. The device is designed for application where both motion tracking and force feedback are required, such as human interaction with virtual environment or rehabilitation tasks. The choice is presented of mechanical structure kinematical equivalent to the structure of the human arm. An actuation system is selected based on braided pneumatic muscle actuators. Antagonistic drive system for each joint is shown, using pulley and cable transmissions. Force/displacement diagrams are presented of two antagonistic acting muscles. Kinematics and dynamic estimations are performed of the system exoskeleton and upper limb. Selected parameters ensure in the antagonistic scheme joint torque regulation and human arm range of motion.

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22

Toan, Tran Huu. "BIO-BASED SUPERVISORY CONTROL OF A LOWER EXOSKELETON FOR STANCE PHASE." Vietnam Journal of Science and Technology 54, no. 3A (March 20, 2018): 115. http://dx.doi.org/10.15625/2525-2518/54/3a/11965.

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This paper presents a newly supervisory impedance control strategy of a wearable lower limb exoskeleton in stance phase intended to enhance human performance and support load-carrying using biomechanical analysis. In order to control the coupled human-robot system, the impedance control strategy, previously developed by the authors for swing phase, has been herein expanded up to the stance phase by regulating the desired impedance between the exoskeleton and a wearer's limb according to a specific motion speed. The effect of human behaviours on the change of impedance parameters across variable walking speeds in the stance phase is adopted to design the fuzzy rules for the control strategy. The control performance of the designed exoskeleton is evaluated on a bench-testing over different ranges of walking speeds (about 0.3 m/s to 1.2 m/s). Experimental results show that the resulting interaction torque, the human-exoskeleton tracking error, and electrical power consumption are significantly reduced as compared to a traditional impedance control, especially in the stance phase. Besides that, an average of 72.3 % of the load was transferred to the ground by the exoskeleton during the stance phase of walking. The developed control strategy on the lower exoskeleton has the potential to increase comfort and adaptation to users during daily use.

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Gull, Muhammad Ahsan, Mikkel Thoegersen, Stefan Hein Bengtson, Mostafa Mohammadi, Lotte N. S. Andreasen Struijk, Thomas B. Moeslund, Thomas Bak, and Shaoping Bai. "A 4-DOF Upper Limb Exoskeleton for Physical Assistance: Design, Modeling, Control and Performance Evaluation." Applied Sciences 11, no. 13 (June 24, 2021): 5865. http://dx.doi.org/10.3390/app11135865.

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Wheelchair mounted upper limb exoskeletons offer an alternative way to support disabled individuals in their activities of daily living (ADL). Key challenges in exoskeleton technology include innovative mechanical design and implementation of a control method that can assure a safe and comfortable interaction between the human upper limb and exoskeleton. In this article, we present a mechanical design of a four degrees of freedom (DOF) wheelchair mounted upper limb exoskeleton. The design takes advantage of non-backdrivable mechanism that can hold the output position without energy consumption and provide assistance to the completely paralyzed users. Moreover, a PD-based trajectory tracking control is implemented to enhance the performance of human exoskeleton system for two different tasks. Preliminary results are provided to show the effectiveness and reliability of using the proposed design for physically disabled people.

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24

Bastide, S., N. Vignais, F. Geffard, and B. Berret. "Analysing human-exoskeleton interaction: on the human adaptation to modified gravito-inertial dynamics." Computer Methods in Biomechanics and Biomedical Engineering 22, sup1 (October 3, 2019): S507—S509. http://dx.doi.org/10.1080/10255842.2020.1714999.

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25

Zha, Shijia, Tianyi Li, Lidan Cheng, Jihua Gu, Wei Wei, Xichuan Lin, and Shaofei Gu. "Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm." Applied Bionics and Biomechanics 2021 (January 21, 2021): 1–13. http://dx.doi.org/10.1155/2021/8850348.

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The prediction of sensor data can help the exoskeleton control system to get the human motion intention and target position in advance, so as to reduce the human-machine interaction force. In this paper, an improved method for the prediction algorithm of exoskeleton sensor data is proposed. Through an algorithm simulation test and two-link simulation experiment, the algorithm improves the prediction accuracy by 14.23 ± 0.5%, and the sensor data is smooth. Input the predicted signal into the two-link model, and use the calculated torque method to verify the prediction accuracy data and smoothness. The simulation results showed that the algorithm can predict the joint angle of the human body and can be used for the follow-up control of the swinging legs of the exoskeleton.

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Song, Jiyuan, Aibin Zhu, Yao Tu, and Jiajun Zou. "Multijoint passive elastic spine exoskeleton for stoop lifting assistance." International Journal of Advanced Robotic Systems 18, no. 6 (November 1, 2021): 172988142110620. http://dx.doi.org/10.1177/17298814211062033.

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In the task of carrying heavy objects, it is easy to cause back injuries and other musculoskeletal diseases. Although wearable robots are designed to reduce this danger, most existing exoskeletons use high-stiffness mechanisms, which are beneficial to load-bearing conduction, but this restricts the natural movement of the human body, thereby causing ergonomic risks. This article proposes a back exoskeleton composed of multiple elastic spherical hinges inspired by the biological spine. This spine exoskeleton can assist in the process of bending the body and ensure flexibility. We deduced the kinematics model of this mechanism and established an analytical biomechanical model of human–robot interaction. The mechanism of joint assistance of the spine exoskeleton was discussed, and experiments were conducted to verify the flexibility of the spine exoskeleton and the effectiveness of the assistance during bending.

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27

Li, Guoxin, Zhijun Li, and Zhen Kan. "Assimilation Control of a Robotic Exoskeleton for Physical Human-Robot Interaction." IEEE Robotics and Automation Letters 7, no. 2 (April 2022): 2977–84. http://dx.doi.org/10.1109/lra.2022.3144537.

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28

Knaepen, Kristel, Pieter Beyl, Saartje Duerinck, Friso Hagman, and Romain Meeusen. "Human-Robot Interaction during Walking with a Powered Compliant Knee Exoskeleton." BIO Web of Conferences 1 (2011): 00049. http://dx.doi.org/10.1051/bioconf/20110100049.

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29

Moreno, Juan C., Fernando Brunetti, Enrique Navarro, Arturo Forner-Cordero, and José L. Pons. "Analysis of the human interaction with a wearable lower-limb exoskeleton." Applied Bionics and Biomechanics 6, no. 2 (July 27, 2009): 245–56. http://dx.doi.org/10.1080/11762320902823324.

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30

Li, Zhijun, Bo Huang, Zhifeng Ye, Mingdi Deng, and Chenguang Yang. "Physical Human–Robot Interaction of a Robotic Exoskeleton By Admittance Control." IEEE Transactions on Industrial Electronics 65, no. 12 (December 2018): 9614–24. http://dx.doi.org/10.1109/tie.2018.2821649.

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31

Jatsun, S. F., A. V. Malchikov, А. А. Postolny, and A. S. Yatsun. "Simulation of Control System of Executive Links of Rehabilitation Exoskeleton Considering Spasticity Effect." Proceedings of the Southwest State University 25, no. 3 (January 29, 2022): 103–19. http://dx.doi.org/10.21869/2223-1560-2021-25-3-103-119.

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Purpose of research. Mathematical modeling of the adaptive control system of the rehabilitation exoskeleton complex, which allows considering the effects of human interaction with the actuators of the drive system, including detecting the appearance of the spasticity effect. The authors of this work solve the following problems: development of human-machine interaction concept, description of the information infrastructure of the exoskeleton complex; development of a structure of an adaptive control system that allows to take into account the interaction of a person with a robot in the process of movement; development of a mathematical model of a man-machine system (MMS) and setting up computational experiments in order to develop adaptive control algorithms under various conditions, development of a method for detecting a spasticity phenomenon and an algorithm of an adaptive control system providing patient safety.Methods. When constructing a mathematical model of the MMS, biomechanical and physiological properties of the manipulation object, mechanical properties of power elements of the structure, as well as features of the operation of the information system of electromechanical device are considered. The work uses mathematical model represented by a system of differential equations of the second order, describing the dynamics of the joint movement of executive links of the exoskeleton and the limb of the operator.Results. During numerical simulation time diagrams of rotation angles changes of exoskeleton links and operator's leg, laws of torques changes in hinges and forces on cuffs characterizing man-machine interaction under various modes and conditions of device functioning are obtained.Conclusion. Conclusions were drawn on applicability of the proposed algorithms of adaptive control system under various modes and conditions of exoskeleton complex functioning, including for rehabilitation of patients with the possibility of spasticity. The conclusions were drawn based on the obtained results of mathematical modeling of MMS functioning.

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Jin, Xinglai, Shiqiang Zhu, Xiaocong Zhu, Qingcheng Chen, and Xuequn Zhang. "Single-input adaptive fuzzy sliding mode control of the lower extremity exoskeleton based on human–robot interaction." Advances in Mechanical Engineering 9, no. 2 (February 2017): 168781401668666. http://dx.doi.org/10.1177/1687814016686665.

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This article introduces a human–robot interaction controller toward the lower extremity exoskeleton whose aim is to improve the tracking performance and drive the exoskeleton to shadow the wearer with less interaction force. To acquire the motion intention of the wearer, two subsystems are designed: the first is to infer the wearer is in which phase based on floor reaction force detected by a multi-sensor system installed in the sole, and the second is to infer the motion velocity based on the multi-axis force sensor and admittance model. An improved single-input fuzzy sliding mode controller is designed, and the adaptive switching controller is combined to promote the tracking performance considering system uncertainties. Adaptation laws are designed based on the Lyapunov stability theorem. Therefore, the stability of the single-input adaptive fuzzy sliding mode control can be guaranteed. Finally, the proposed methods are applied to the lower extremity exoskeleton, especially in the swing phase. Its effectiveness is validated by comparative experiments.

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Yang, Wei, Jiyu Zhang, Sheng Zhang, and Canjun Yang. "Lower Limb Exoskeleton Gait Planning Based on Crutch and Human-Machine Foot Combined Center of Pressure." Sensors 20, no. 24 (December 16, 2020): 7216. http://dx.doi.org/10.3390/s20247216.

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With the help of wearable robotics, the lower limb exoskeleton becomes a promising solution for spinal cord injury (SCI) patients to recover lower body locomotion ability. However, fewer exoskeleton gait planning methods can meet the needs of patient in real time, e.g., stride length or step width, etc., which may lead to human-machine incoordination, limit comfort, and increase the risk of falling. This work presents a human-exoskeleton-crutch system with the center of pressure (CoP)-based gait planning method to enable the balance control during the exoskeleton-assisted walking with crutches. The CoP generated by crutches and human-machine feet makes it possible to obtain the overall stability conditions of the system in the process of exoskeleton-assisted quasi-static walking, and therefore, to determine the next stride length and ensure the balance of the next step. Thus, the exoskeleton gait is planned with the guidance of stride length. It is worth emphasizing that the nominal reference gait is adopted as a reference to ensure that the trajectory of the swing ankle mimics the reference one well. This gait planning method enables the patient to adaptively interact with the exoskeleton gait. The online gait planning walking tests with five healthy volunteers proved the method’s feasibility. Experimental results indicate that the algorithm can deal with the sensed signals and plan the landing point of the swing leg to ensure balanced and smooth walking. The results suggest that the method is an effective means to improve human–machine interaction. Additionally, it is meaningful for the further training of independent walking stability control in exoskeletons for SCI patients with less assistance of crutches.

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Dao, Quy-Thinh, Van-Vuong Dinh, Minh-Chien Trinh, Viet-Cuong Tran, Van-Linh Nguyen, Minh-Duc Duong, and Ngoc-Tam Bui. "Nonlinear Extended Observer-Based ADRC for a Lower-Limb PAM-Based Exoskeleton." Actuators 11, no. 12 (December 8, 2022): 369. http://dx.doi.org/10.3390/act11120369.

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In lower-limb rehabilitation systems, exoskeleton robots are one of the most important components. These robots help patients to execute repetitive exercises under the guidance of physiotherapists. Recently, pneumatic artificial muscles (PAM), a kind of actuator that acts similarly to human muscles, have been chosen to power the exoskeleton robot for better human–machine interaction. In order to enhance the performance of a PAM-based exoskeleton robot, this article implements an active disturbance rejection control (ADRC) strategy with a nonlinear extended state observer (NLESO). Moreover, the stability of the closed-loop system is proved by Lyapunov’s theory. Finally, the experimental results show that with the proposed control strategy, the rehabilitation robot can effectively track the desired trajectories even when under external disturbance.

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35

Islam, Md Rasedul, Md Assad-Uz-Zaman, Brahim Brahmi, Yassine Bouteraa, Inga Wang, and Mohammad Habibur Rahman. "Design and Development of an Upper Limb Rehabilitative Robot with Dual Functionality." Micromachines 12, no. 8 (July 24, 2021): 870. http://dx.doi.org/10.3390/mi12080870.

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The design of an upper limb rehabilitation robot for post-stroke patients is considered a benchmark problem regarding improving functionality and ensuring better human–robot interaction (HRI). Existing upper limb robots perform either joint-based exercises (exoskeleton-type functionality) or end-point exercises (end-effector-type functionality). Patients may need both kinds of exercises, depending on the type, level, and degree of impairments. This work focused on designing and developing a seven-degrees-of-freedom (DoFs) upper-limb rehabilitation exoskeleton called ‘u-Rob’ that functions as both exoskeleton and end-effector types device. Furthermore, HRI can be improved by monitoring the interaction forces between the robot and the wearer. Existing upper limb robots lack the ability to monitor interaction forces during passive rehabilitation exercises; measuring upper arm forces is also absent in the existing devices. This research work aimed to develop an innovative sensorized upper arm cuff to measure the wearer’s interaction forces in the upper arm. A PID control technique was implemented for both joint-based and end-point exercises. The experimental results validated both types of functionality of the developed robot.

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Li, Xinwei, Su Liu, Ying Chang, Sujiao Li, Yuanjie Fan, and Hongliu Yu. "A Human Joint Torque Estimation Method for Elbow Exoskeleton Control." International Journal of Humanoid Robotics 17, no. 03 (March 11, 2020): 1950039. http://dx.doi.org/10.1142/s0219843619500397.

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Exoskeleton for motion assistance has obtained more and more attention due to its advantages in rehabilitation and assistance for daily life. This research designed an estimation method of human joint torque by the kinetic human–machine interaction between the operator’s elbow joint torque and the output of exoskeleton. The human elbow joint torque estimation was obtained by back propagation (BP) neural network with physiological and physical input elements including shoulder posture, elbow joint-related muscles activation, elbow joint position, and angular velocity. An elbow-powered exoskeleton was developed to verify the validity of the human elbow joint torque estimation. The average correlation coefficients of estimated and measured three shoulder joint angles are 97.9%, 96.2%, and 98.1%, which show that estimated joint angles are consistent with the measured joint angle. The average root-mean-square error between estimated elbow joint torque and measured values is about 0.143[Formula: see text]N[Formula: see text]m. The experiment results proved that the proposed strategy had good performance in human joint torque estimation.

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37

Caulcrick, Christopher, Weiguang Huo, Will Hoult, and Ravi Vaidyanathan. "Human Joint Torque Modelling With MMG and EMG During Lower Limb Human-Exoskeleton Interaction." IEEE Robotics and Automation Letters 6, no. 4 (October 2021): 7185–92. http://dx.doi.org/10.1109/lra.2021.3097832.

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38

ROSEN, JACOB, and JOEL C. PERRY. "UPPER LIMB POWERED EXOSKELETON." International Journal of Humanoid Robotics 04, no. 03 (September 2007): 529–48. http://dx.doi.org/10.1142/s021984360700114x.

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An exoskeleton is a wearable robot with joints and links corresponding to those of the human body. With applications in rehabilitation medicine, virtual reality simulation, and teleoperation, exoskeletons offer benefits for both disabled and healthy populations. Analytical and experimental approaches were used to develop, integrate, and study a powered exoskeleton for the upper limb and its application as an assistive device. The kinematic and dynamic dataset of the upper limb during daily living activities was one among several factors guiding the development of an anthropomorphic, seven degree-of-freedom, powered arm exoskeleton. Additional design inputs include anatomical and physiological considerations, workspace analyses, and upper limb joint ranges of motion. Proximal placement of motors and distal placement of cable-pulley reductions were incorporated into the design, leading to low inertia, high-stiffness links, and back-drivable transmissions with zero backlash. The design enables full glenohumeral, elbow, and wrist joint functionality. Establishing the human-machine interface at the neural level was facilitated by the development of a Hill-based muscle model (myoprocessor) that enables intuitive interaction between the operator and the wearable robot. Potential applications of the exoskeleton as a wearable robot include (i) an assistive (orthotic) device for human power amplifications, (ii) a therapeutic and diagnostics device for physiotherapy, (iii) a haptic device in virtual reality simulation, and (iv) a master device for teleoperation.

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Schwartz, Mathilde, Jean Theurel, and Kévin Desbrosses. "Effectiveness of Soft versus Rigid Back-Support Exoskeletons during a Lifting Task." International Journal of Environmental Research and Public Health 18, no. 15 (July 29, 2021): 8062. http://dx.doi.org/10.3390/ijerph18158062.

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This study investigated the influence of passive back-support exoskeletons (EXOBK) design, trunk sagittal inclination (TSI), and gender on the effectiveness of an exoskeleton to limit erector spinae muscle (ES) activation during a sagittal lifting/lowering task. Twenty-nine volunteers performed an experimental dynamic task with two exoskeletons (two different designs: soft (SUIT) and rigid (SKEL)), and without equipment (FREE). The ES activity was analyzed for eight parts of TSI, each corresponding to 25% of the range of motion (lifting: P1 to P4; lowering: P5 to P8). The impact of EXOBK on ES activity depended on the interaction between exoskeleton design and TSI. With SKEL, ES muscle activity significantly increased for P8 (+36.8%) and tended to decrease for P3 (−7.2%, p = 0.06), compared to FREE. SUIT resulted in lower ES muscle activity for P2 (−9.6%), P3 (−8.7%, p = 0.06), and P7 (−11.1%), in comparison with FREE. Gender did not influence the effect of either back-support exoskeletons on ES muscle activity. These results point to the need for particular attention with regard to (1) exoskeleton design (rigid versus soft) and to (2) the range of trunk motion, when selecting an EXOBK. In practice, the choice of a passive back-support exoskeleton, between rigid and soft design, requires an evaluation of human-exoskeleton interaction in real task conditions. The characterization of trunk kinematics and ranges of motion appears essential to identify the benefits and the negative effects to take into account with each exoskeleton design.

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Chen, Shan, Tenghui Han, Fangfang Dong, Lei Lu, Haijun Liu, Xiaoqing Tian, and Jiang Han. "Precision Interaction Force Control of an Underactuated Hydraulic Stance Leg Exoskeleton Considering the Constraint from the Wearer." Machines 9, no. 5 (May 10, 2021): 96. http://dx.doi.org/10.3390/machines9050096.

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Hydraulic lower limb exoskeletons are wearable robotic systems, which can help people carry heavy loads. Recently, underactuated exoskeletons with some passive joints have been developed in large numbers for the purpose of decreasing the weight and energy consumption of the system. There are many control algorithms for a multi-joint fully actuated exoskeleton, which cannot be applied for underactuated systems due to the reduction in the number of control inputs. Besides, since the hydraulic actuator is not a desired force output source, there exist high order nonlinearities in hydraulic exoskeletons, which makes the controller design more challenging than motor driven exoskeleton systems. This paper proposed a precision interaction force controller for a 3DOF underactuated hydraulic stance leg exoskeleton. First, the control effect of the wearer is considered and the posture of the exoskeleton back is assumed as a desired trajectory under the control of the wearer. Under this assumption, the system dynamics are changed from a 3DOF underactuated system in joint space to a 2DOF fully actuated system in Cartesian space. Then, a three-level interaction force controller is designed in which the high-level controller conducts human motion intent inference, the middle level controller tracks human motion and the low-level controller achieves output force tracking of hydraulic cylinders. The MIMO adaptive robust control algorithm is applied in the controller design to effectively address the high order nonlinearities of the hydraulic system, multi-joint couplings and various model uncertainties. A gain tuning method is also provided to facilitate the controller gains selection for engineers. Comparative simulations are conducted, which demonstrate that the principal human-machine interaction force components can be minimized and good robust performance to load change and modeling errors can be achieved.

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Kladovasilakis, Nikolaos, Ioannis Kostavelis, Paschalis Sideridis, Eleni Koltzi, Konstantinos Piliounis, Dimitrios Tzetzis, and Dimitrios Tzovaras. "A Novel Soft Robotic Exoskeleton System for Hand Rehabilitation and Assistance Purposes." Applied Sciences 13, no. 1 (December 30, 2022): 553. http://dx.doi.org/10.3390/app13010553.

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During the last decade, soft robotic systems, such as actuators and grippers, have been employed in various commercial applications. Due to the need to integrate robotic mechanisms into devices operating alongside humans, soft robotic systems concentrate increased scientific interest in tasks with intense human–robot interaction, especially for human-exoskeleton applications. Human exoskeletons are usually utilized for assistance and rehabilitation of patients with mobility disabilities and neurological disorders. Towards this direction, a fully functional soft robotic hand exoskeleton system was designed and developed, utilizing innovative air-pressurized soft actuators fabricated via additive manufacturing technologies. The CE-certified system consists of a control glove that copies the motion from the healthy hand and passes the fingers configuration to the exoskeleton applied on the affected hand, which consists of a soft exoskeleton glove (SEG) controlled with the assistance of one-axis flex sensors, micro-valves, and a proportional integral derivative (PID) controller. Each finger of the SEG moves independently due to the finger-dedicated motion control system. Furthermore, the real-time monitoring and control of the fabricated SEG are conducted via the developed software. In addition, the efficiency of the exoskeleton system was investigated through an experimental validation procedure with the involvement of healthy participants (control group) and patients, which evaluated the efficiency of the system, including safety, ergonomics, and comfort in its usage.

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42

Noda, Tomoyuki, Sang-Ho Hyon, and Jun Morimoto. "Exoskeleton assistive robot: Learning feedforward assist model iteratively through human–robot interaction." Neuroscience Research 71 (September 2011): e410. http://dx.doi.org/10.1016/j.neures.2011.07.1796.

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43

Song, Guangkui, Rui Huang, Jing Qiu, Hong Cheng, and Shuai Fan. "Model-based Control with Interaction Predicting for Human-coupled Lower Exoskeleton Systems." Journal of Intelligent & Robotic Systems 100, no. 2 (April 23, 2020): 389–400. http://dx.doi.org/10.1007/s10846-020-01200-5.

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44

Ka, Duong Mien, Cheng Hong, Tran Huu Toan, and Jing Qiu. "Minimizing human-exoskeleton interaction force by using global fast sliding mode control." International Journal of Control, Automation and Systems 14, no. 4 (April 15, 2016): 1064–73. http://dx.doi.org/10.1007/s12555-014-0395-7.

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Ren, Bin, Xurong Luo, and Jiayu Chen. "Single Leg Gait Tracking of Lower Limb Exoskeleton Based on Adaptive Iterative Learning Control." Applied Sciences 9, no. 11 (May 31, 2019): 2251. http://dx.doi.org/10.3390/app9112251.

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The lower limb exoskeleton is a wearable human–robot interactive equipment, which is tied to human legs and moves synchronously with the human gait. Gait tracking accuracy greatly affects the performance and safety of the lower limb exoskeletons. As the human–robot coupling systems are usually nonlinear and generate unpredictive errors, a conventional iterative controller is regarded as not suitable for safe implementation. Therefore, this study proposed an adaptive control mechanism based on the iterative learning model to track the single leg gait for lower limb exoskeleton control. To assess the performance of the proposed method, this study implemented the real lower limb gait trajectory that was acquired with an optical motion capturing system as the control inputs and assessment benchmark. Then the impact of the human–robot interaction torque on the tracking error was investigated. The results show that the interaction torque has an inevitable impact on the tracking error and the proposed adaptive iterative learning control (AILC) method can effectively reduce such error without sacrificing the iteration efficiency.

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46

Hu, Bingshan, Fuchao Zhang, Hongrun Lu, Huaiwu Zou, Jiantao Yang, and Hongliu Yu. "Design and Assist-as-Needed Control of Flexible Elbow Exoskeleton Actuated by Nonlinear Series Elastic Cable Driven Mechanism." Actuators 10, no. 11 (October 29, 2021): 290. http://dx.doi.org/10.3390/act10110290.

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Анотація:

Exoskeletons can assist the daily life activities of the elderly with weakened muscle strength, but traditional rigid exoskeletons bring parasitic torque to the human joints and easily disturbs the natural movement of the wearer’s upper limbs. Flexible exoskeletons have more natural human-machine interaction, lower weight and cost, and have great application potential. Applying assist force according to the patient’s needs can give full play to the wearer’s remaining muscle strength, which is more conducive to muscle strength training and motor function recovery. In this paper, a design scheme of an elbow exoskeleton driven by flexible antagonistic cable actuators is proposed. The cable actuator is driven by a nonlinear series elastic mechanism, in which the elastic elements simulate the passive elastic properties of human skeletal muscle. Based on an improved elbow musculoskeletal model, the assist torque of exoskeleton is predicted. An assist-as-needed (AAN) control algorithm is proposed for the exoskeleton and experiments are carried out. The experimental results on the experimental platform show that the root mean square error between the predicted assist torque and the actual assist torque is 0.00226 Nm. The wearing experimental results also show that the AAN control method designed in this paper can reduce the activation of biceps brachii effectively when the exoskeleton assist level increases.

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Jois, Himavath, and Alan R. Wagner. "What Happens When Robots Punish? Evaluating Human Task Performance During Robot-Initiated Punishment." ACM Transactions on Human-Robot Interaction 10, no. 4 (December 31, 2021): 1–18. http://dx.doi.org/10.1145/3472207.

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This article examines how people respond to robot-administered verbal and physical punishments. Human participants were tasked with sorting colored chips under time pressure and were punished by a robot when they made mistakes, such as inaccurate sorting or sorting too slowly. Participants were either punished verbally by being told to stop sorting for a fixed time, or physically, by restraining their ability to sort with an in-house crafted robotic exoskeleton. Either a human experimenter or the robot exoskeleton administered punishments, with participant task performance and subjective perceptions of their interaction with the robot recorded. The results indicate that participants made more mistakes on the task when under the threat of robot-administered punishment. Participants also tended to comply with robot-administered punishments at a lesser rate than human-administered punishments, which suggests that humans may not afford a robot the social authority to administer punishments. This study also contributes to our understanding of compliance with a robot and whether people accept a robot’s authority to punish. The results may influence the design of robots placed in authoritative roles and promote discussion of the ethical ramifications of robot-administered punishment.

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Zha, Fusheng, Wentao Sheng, Wei Guo, Shiyin Qiu, Jing Deng, and Xin Wang. "Dynamic Parameter Identification of a Lower Extremity Exoskeleton Using RLS-PSO." Applied Sciences 9, no. 2 (January 17, 2019): 324. http://dx.doi.org/10.3390/app9020324.

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The lower extremity exoskeleton is a device for auxiliary assistance of human movement. The interaction performance between the exoskeleton and the human is determined by the lower extremity exoskeleton’s controller. The performance of the controller is affected by the accuracy of the dynamic equation. Therefore, it is necessary to study the dynamic parameter identification of lower extremity exoskeleton. The existing dynamic parameter identification algorithms for lower extremity exoskeletons are generally based on Least Square (LS). There are some internal drawbacks, such as complicated experimental processes and low identification accuracy. A dynamic parameter identification algorithm based on Particle Swarm Optimization (PSO) with search space defined by Recursive Least Square (RLS) is developed in this investigation. The developed algorithm is named RLS-PSO. By defining the search space of PSO, RLS-PSO not only avoids the convergence of identified parameters to the local minima, but also improves the identification accuracy of exoskeleton dynamic parameters. Under the same experimental conditions, the identification accuracy of RLS-PSO, PSO and LS was quantitatively compared and analyzed. The results demonstrated that the identification accuracy of RLS-PSO is higher than that of LS and PSO.

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Li, Ning, Tie Yang, Yang Yang, Peng Yu, Xiujuan Xue, Xingang Zhao, Guoli Song, et al. "Bioinspired Musculoskeletal Model-based Soft Wrist Exoskeleton for Stroke Rehabilitation." Journal of Bionic Engineering 17, no. 6 (November 2020): 1163–74. http://dx.doi.org/10.1007/s42235-020-0101-9.

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AbstractExoskeleton robots have demonstrated the potential to rehabilitate stroke dyskinesia. Unfortunately, poor human-machine physiological coupling causes unexpected damage to human of muscles and joints. Moreover, inferior humanoid kinematics control would restrict human natural kinematics. Failing to deal with these problems results in bottlenecks and hinders its application. In this paper, the simplified muscle model and muscle-liked kinematics model were proposed, based on which a soft wrist exoskeleton was established to realize natural human interaction. Firstly, we simplified the redundant muscular system related to the wrist joint from ten muscles to four, so as to realize the human-robot physiological coupling. Then, according to the above human-like musculoskeletal model, the humanoid distributed kinematics control was established to achieve the two DOFs coupling kinematics of the wrist. The results show that the wearer of an exoskeleton could reduce muscle activation and joint force by 43.3% and 35.6%, respectively. Additionally, the humanoid motion trajectories similarity of the robot reached 91.5%. Stroke patients could recover 90.3% of natural motion ability to satisfy for most daily activities. This work provides a fundamental understanding on human-machine physiological coupling and humanoid kinematics control of the exoskeleton robots for reducing the post-stroke complications.

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Yang, Peng, Gaowei Zhang, Jie Wang, Xiaozhou Wang, Lili Zhang, and Lingling Chen. "Command Filter Backstepping Sliding Model Control for Lower-Limb Exoskeleton." Mathematical Problems in Engineering 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/1064535.

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A command filter adaptive fuzzy backstepping control strategy is proposed for lower-limb assisting exoskeleton. Firstly, the human-robot model is established by taking the human body as a passive part, and a coupling torque is introduced to describe the interaction between the exoskeleton and human leg. Then, Vicon motion capture system is employed to obtain the reference trajectory. For the purpose of obviating the “explosion of complexity” in conventional backstepping, a second-order command filter is introduced into the sliding mode control strategy. The fuzzy logic systems (FLSs) are also applied to handle with the chattering problem by estimating the uncertainties and disturbances. Furthermore, the stability of the closed-loop system is proved based on the Lyapunov theory. Finally, simulation results are presented to illustrate the effectiveness of the control strategy.

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