Article
Engineering, Biomedical
Weihai Chen, Mingxing Lyu, Xilun Ding, Jianhua Wang, Jianbin Zhang
Summary: This paper presents an EMG-based gait pattern adaptation method that allows subjects to control a robotic exoskeleton for gait rehabilitation. The results show that the subjects were able to change the gait pattern of the exoskeleton using EMG signals and achieved the adaptation goals within a short period of time. This method enables subjects to actively participate in the rehabilitation training.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Pengbo Huang, Zhijun Li, MengChu Zhou, Xiang Li, Mengyue Cheng
Summary: This article investigates step adjustment in a walking exoskeleton system to enhance human mobility. By considering human walking intention and utilizing an admittance model, the proposed method shapes a reference trajectory for the walking exoskeleton robot to follow. Experiments on healthy subjects demonstrate its effectiveness in improving human mobility when applied to walking exoskeletons.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Curt A. Laubscher, Anthony C. Goo, Jerzy T. Sawicki
Summary: This paper investigates how to define the phase of gait considering the influence of the user. The results show that optimizing the definition improves the progression of phase and makes the commanded reference closer to the desired gait pattern.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Computer Science, Artificial Intelligence
Richa Sharma, Prerna Gaur, Shaurya Bhatt, Deepak Joshi
Summary: This study focuses on the development of a cost-effective lower limb exoskeleton for restoring normal gait in individuals with mobility disorders, stroke, or elderly persons. It uses the dragon fly algorithm to optimize the fuzzy logic control and compares it with genetic algorithm for closed-loop control design. Experimental data validation and robustness testing indicate the effectiveness of the proposed control strategies, especially in bipedal walking scenarios.
APPLIED SOFT COMPUTING
(2021)
Article
Multidisciplinary Sciences
Patrick Slade, Mykel J. Kochenderfer, Scott L. Delp, Steven H. Collins
Summary: Personalized exoskeleton assistance can be optimized rapidly and under real-world conditions using wearable sensors. This approach is equally effective as laboratory methods but much faster. Real-world optimization of ankle exoskeleton assistance can significantly improve walking speed and energy economy.
Article
Engineering, Electrical & Electronic
Lingzhou Yu, Harun Leto, Shaoping Bai
Summary: This paper introduces an assistive lower-limb exoskeleton (ALEXO) for active walking assistance. The development of the ALEXO including mechanical design, sensors and gait control is described. The effectiveness of the developed exoskeleton with the proposed control method for walking assistance is demonstrated through simulations and system tests.
Article
Engineering, Biomedical
Seungmoon Song, Steven H. Collins
Summary: In this study, human-in-the-loop optimization was used to demonstrate that ankle exoskeleton assistance can lead to significant increases in self-selected walking speed. By optimizing torque for speed, participants walked 42% faster than in normal shoes, highlighting the potential benefits for individuals with reduced walking speed.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2021)
Article
Robotics
Bokman Lim, Byungjune Choi, Changhyun Roh, Seungyong Hyung, Yong-Jae Kim, Younbaek Lee
Summary: This letter introduces a parametric delayed output feedback controller for human-exoskeleton interactions during walking or running. The controller utilizes three adjustable parameters to generate various interaction torques and has been tested for reliability and efficacy. Results show that hip exoskeleton assistance can reduce metabolic cost during running, and different gait resistances can be provided using different time delays.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Multidisciplinary Sciences
Michael Shepertycky, Sarah Burton, Andrew Dickson, Yan-Fei Liu, Qingguo Li
Summary: Evolutionary pressures have shaped human walking patterns to be highly energy-efficient, posing challenges for exoskeletons to reduce metabolic costs. However, some exoskeletons have successfully reduced metabolic expenditure by strategically removing kinetic energy during the gait cycle and converting it into electrical power. Timing and magnitude of energy removal are critical factors for effective metabolic cost reduction, as demonstrated through comparison of different loading profiles.
Article
Biotechnology & Applied Microbiology
Benjamin A. Shafer, Sasha A. Philius, Richard W. Nuckols, James McCall, Aaron J. Young, Gregory S. Sawicki
Summary: Powered ankle exoskeletons can reduce metabolic cost by applying assistive torques with optimized timing and magnitude. Continuous adaptation of torque assistance is necessary for exoskeleton controllers. Using a neuromuscular model can help optimize the parameters of exoskeleton controllers for improved performance.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Automation & Control Systems
Jonathan Casas, Chen-Hao Chang, Victor H. Duenas
Summary: This article presents a learning-based strategy for interaction with a hybrid exoskeleton during treadmill walking. An adaptive control approach and functional electrical stimulation (FES) are used to provide joint assistance and activate muscles. Experimental results demonstrate that the learning controller outperforms classical adaptive control in terms of performance and parameter convergence speed.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Automation & Control Systems
Yaohui Sun, Jiangping Hu, Zhinan Peng, Bijoy K. Ghosh
Summary: This paper presents a hierarchical critic learning optimal control strategy for lower limb exoskeleton systems with prescribed state constraints. The strategy transforms the constrained state into an equivalent new unconstrained state and utilizes dynamic movement primitives to estimate human motion intentions for optimal control. Simulation results validate the effectiveness of the proposed strategy.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Biochemical Research Methods
Nicholas A. Bianco, Steven H. Collins, Karen Liu, Scott L. Delp
Summary: Walking balance is crucial for independent mobility, but falls due to loss of balance are a leading cause of death among the elderly. Exoskeleton assistance could help individuals with neuromuscular deficits by providing stabilizing torques at lower-limb joints. However, the effects of exoskeleton torques on walking kinematics are still unclear.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Multidisciplinary Sciences
Rachel Hybart, K. Siena Villancio-Wolter, Daniel Perry Ferris
Summary: This study tested the effects of robotic ankle exoskeletons under proportional myoelectric control on the cost of transport of walking both on a treadmill and outside. The results showed no significant increase or decrease in the cost of transport when walking with the exoskeletons compared to walking without them. Future research should consider how more difficult tasks affect the cost of transport while walking with and without robotic ankle exoskeletons.
Article
Engineering, Biomedical
Cristina Bayon, Arvid Q. L. Keemink, Michelle van Mierlo, Wolfgang Rampeltshammer, Herman van der Kooij, Edwin H. F. van Asseldonk
Summary: This study proposes a cooperative ankle-exoskeleton control strategy and evaluates its effectiveness in able-bodied participants. The results demonstrate that the proposed controller reduces participants' effort while maintaining their ability to counteract balance disturbances. Significant reductions in muscle activity were observed, indicating the potential of this strategy in supporting and improving balance control in individuals with motor disabilities.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2022)
Article
Automation & Control Systems
Runwei Guan, Shanliang Yao, Lulu Liu, Xiaohui Zhu, Ka Lok Man, Yong Yue, Jeremy Smith, Eng Gee, Yutao Yue
Summary: With the development of Unmanned Surface Vehicles (USVs), the perception of inland waterways has become significant. Traditional RGB cameras cannot work effectively in adverse weather and at night, which has led to the emergence of 4D millimeter-wave radar as a new perception sensor. However, the radar suffers from water-surface clutter and irregular shape of point cloud. To address these issues, this paper proposes a high-performance panoptic perception model called Mask-VRDet, which fuses features of vision and radar using graph neural network.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Adrien Le Reun, Kevin Subrin, Anthony Dubois, Sebastien Garnier
Summary: This study aims to evaluate the quality and health of aerospace parts using a high-dimensional robotic cell. By utilizing X-ray Computed Tomography devices, the interior of the parts can be reconstructed and anomalies can be detected. A methodology is proposed to assess both the raw process capability and the improved process capability, with three strategies developed to improve the robot behavior model and calibration.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Weiming Ba, Jung-Che Chang, Jing Liu, Xi Wang, Xin Dong, Dragos Axinte
Summary: This paper proposes a hybrid scheme for kinematic control of continuum robots, which avoids errors through tension supervision and accurate piecewise linear approximation. The effectiveness of the controller is verified on different continuum robotic systems.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Gabriele Abbate, Alessandro Giusti, Viktor Schmuck, Oya Celiktutan, Antonio Paolillo
Summary: In this study, a learning-based approach is proposed to predict the probability of human users interacting with a robot before the interaction begins. By considering the pose and motion of the user, the approach labels the robot's encounters with humans in a self-supervised manner. The method is validated and deployed in various scenarios, achieving high accuracy in predicting user intentions to interact with the robot.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Tiago Cortinhal, Eren Erdal Aksoy
Summary: This work presents a new depth-and semantics-aware conditional generative model, named TITAN-Next, for cross-domain image-to-image translation between LiDAR and camera sensors. The model is able to translate raw LiDAR point clouds to RGB-D camera images by solely relying on semantic scene segments, and it has practical applications in fields like autonomous vehicles.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Marios Krestenitis, Emmanuel K. Raptis, Athanasios Ch. Kapoutsis, Konstantinos Ioannidis, Elias B. Kosmatopoulos, Stefanos Vrochidis
Summary: This paper addresses the issue of informative path planning for a UAV used in precision agriculture. By using a non-uniform scanning approach, the time spent in areas with minimal value is reduced, while maintaining high precision in information-dense regions. A novel active sensing and deep learning-based coverage path planning approach is proposed, which adjusts the UAV's speed based on the quantity and confidence level of identified plant classes.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shota Kokubu, Pablo E. Tortos Vinocour, Wenwei Yu
Summary: In this study, a new modular soft actuator was proposed to improve the support performance of soft rehabilitation gloves (SRGs). Objective evaluations and clinical tests were conducted to demonstrate the effectiveness and functionality of the proposed actuator and SRG.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Jinliang Zhu, Yuanxi Sun, Jie Xiong, Yiyang Liu, Jia Zheng, Long Bai
Summary: This paper proposes an active prosthetic knee joint with a variable stiffness parallel elastic actuation mechanism. Numerical verifications and practical experiments demonstrate that the mechanism can reduce torque and power, thus reducing energy consumption and improving the endurance of the prosthetic knee joint.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Yong You, Jingtao Wu, Yunlong Meng, Dongye Sun, Datong Qin
Summary: A new power-cycling variable transmission (PCVT) is proposed and applied to construction vehicles to improve transmission efficiency. A shift correction strategy is developed based on identifying the changes in construction vehicles' mass and gradient. Simulation results show that the proposed method can correct shift points, improve operation efficiency, and ensure a safer operation process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shaorui Liu, Wei Tian, Jianxin Shen, Bo Li, Pengcheng Li
Summary: This paper proposes a two-objective optimization technique for multi-robot systems, addressing the issue of balancing productivity and machining performance in high-quality machining tasks.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pengchao Ding, Faben Zhu, Hongbiao Zhu, Gongcheng Wang, Hua Bai, Han Wang, Dongmei Wu, Zhijiang Du, Weidong Wang
Summary: We propose an autonomous approaching scheme for mobile robot traversing obstacle stairwells, which overcomes the restricted field of vision caused by obstacles. The scheme includes stair localization, structural parameter estimation, and optimization of the approaching process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pedro Azevedo, Vitor Santos
Summary: Accurate detection and tracking of vulnerable road users and traffic objects are vital tasks for autonomous driving and driving assistance systems. This paper proposes a solution for object detection and tracking in an autonomous driving scenario, comparing different object detectors and exploring the deployment on edge devices. The effectiveness of DeepStream technology and different object trackers is assessed using the KITTI tracking dataset.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Benjamin Beiter, Divya Srinivasan, Alexander Leonessa
Summary: Powered exoskeletons can significantly reduce physical workload and have great potential impact on future labor practices. To truly assist users in achieving task goals, a shared autonomy control framework is proposed to separate the control objectives of the human and exoskeleton. Positive Power control is introduced for the human-based controller, while 'acceptance' is used as a measure of matching the exoskeleton's control objective to the human's. Both control objectives are implemented in an optimization-based Whole-Body-Control structure. The results verify the effectiveness of the control framework and its potential for improving cooperative control for powered exoskeletons.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)