检索结果-内蒙古大学图书馆

Bionic Design and Kinematic Evaluation of a Stiffness-Adjustable Spinal Exoskeleton for Trunk Support

学校读者我要写书评

暂无评论

Bionic Design and Kinematic Evaluation of a Stiffness-Adjust...

Service robotics (ICoSR), International Conference on

作者： Yuhan Yin Aibin Zhu Peng Xu Jing Zhang Jie Liu Systems and Shaanxi Key Laboratory of Intelligent Robots Institute of Robotics & Intelligent Xi'an Jiaotong University Xi'an China Honghui Hospital Xi'an Jiaotong University Xi'an China School of Mechanical Engineering Yanshan University Qinhuangdao China

ISBN: (数字)9798350367119

ISBN: (纸本)9798350367126

In recent years, the field of medical rehabilitation utilizing back-support exoskeleton has demonstrated significant potential for application. However, existing exoskeletons still present issues such as insufficient comfort and safety. This paper proposes the design of a passive exoskeleton with variable stiffness for supporting the human trunk. The primary structure consists of a symmetrically distributed chain-type configuration on both sides of the spine, allowing for adjustable stiffness to assist users during complex body movements. In comparison to traditional rigid exoskeletons, this design not only enhances flexibility but also improves overall exoskeleton performance. Kinematic analysis of the exoskeleton reveals a high degree of freedom. Experimental results demonstrate that the exoskeleton provides a wide range of motion, with average ranges of 63° flexion, 33° extension, 25° lateral flexion, and 18° axial rotation when worn.

关键词： Service robots Exoskeletons Kinematics Back Safety Motion control

Distributed Banach-Picard Iteration: Application to Distributed EM and Distributed PCA

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Andrade, Francisco Figueiredo, Mário A.T. Xavier, João The Instituto de Telecomunicações Lisbon Portugal The Laboratory for Robotics and Engineering Systems Institute for Systems and Robotics Lisbon Portugal

In recent work, we proposed a distributed Banach-Picard iteration (DBPI) that allows a set of agents, linked by a communication network, to find a fixed point of a locally contractive (LC) map that is the average of individual maps held by said agents. In this work, we build upon the DBPI and its local linear convergence (LLC) guarantees to make several contributions. We show that Sanger’s algorithm for principal component analysis (PCA) corresponds to the iteration of an LC map that can be written as the average of local maps, each map known to each agent holding a subset of the data. Similarly, we show that a variant of the expectation-maximization (EM) algorithm for parameter estimation from noisy and faulty measurements in a sensor network can be written as the iteration of an LC map that is the average of local maps, each available at just one node. Consequently, via the DBPI, we derive two distributed algorithms – distributed EM and distributed PCA – whose LLC guarantees follow from those that we proved for the DBPI. The verification of the LC condition for EM is challenging, as the underlying operator depends on random samples, thus the LC condition is of probabilistic nature. Copyright © 2021, The Authors. All rights reserved.

关键词： Maximum principle

Multi-Feature-Based Online Remaining Useful Life Prediction of Lithium-Ion Batteries in Stages Using Cascaded Data-Driven Algorithm

学校读者我要写书评

暂无评论

SSRN

SSRN 2023年

作者： Tao, Liujun Wu, Huaiyu Zheng, Xiujuan Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology China

Accurate prediction of remaining useful life (RUL) is very important for the safe and stable operation of battery systems. Considering that it is difficult to directly measure the capacity of lithium-ion batteries during operation, this paper proposes an online hybrid cascaded data-driven prediction algorithm for RUL. Firstly, health indicators (HIs) are extracted from the charge-discharge voltage and incremental capacity curves. Then, the correlation between HIs and battery capacity degradation is quantified by grey relational analysis. And kernel principal component analysis is used to eliminate redundant information of HIs. Secondly, the kernel extreme learning machine based on sparrow search algorithm (SSA-KELM) is selected as the first-level capacity prediction model to establish the relationship between HIs and capacity. The bidirectional long short-term memory network is selected as the secondary-level capacity prediction model, which fuses the preliminary capacity predictions of SSA-KELM. Finally, the battery dataset from NASA and Oxford are used to verify the proposed method. The results demonstrate that the proposed method has strong generalization ability and high prediction accuracy. Quantitatively, the RMSE and MAPE of NASA batteries are within 0.03, while the errors of Oxford batteries are within 0.003. The RUL prediction errors of all lithium-ion batteries are within two cycles. © 2023, The Authors. All rights reserved.

关键词： Lithium-ion batteries

Whole-body MPC for highly redundant legged manipulators: experimental evaluation with a 37 DoF dual-arm quadruped

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Dadiotis, Ioannis Laurenzi, Arturo Tsagarakis, Nikos Humanoid and Human-Centered Mechatronics Research Line Italian Institute of Technology Genoa16163 Italy The Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa16145 Italy

Recent progress in legged locomotion has rendered quadruped manipulators a promising solution for performing tasks that require both mobility and manipulation (loco-manipulation). In the real world, task specifications and/or environment constraints may require the quadruped manipulator to be equipped with high redundancy as well as whole-body motion coordination capabilities. This work presents an experimental evaluation of a whole-body Model Predictive Control (MPC) framework achieving real-time performance on a dual-arm quadruped platform consisting of 37 actuated joints. To the best of our knowledge this is the legged manipulator with the highest number of joints to be controlled with real-time whole-body MPC so far. The computational efficiency of the MPC while considering the full robot kinematics and the centroidal dynamics model builds upon an open-source DDP-variant solver and a state-of-the-art optimal control problem formulation. Differently from previous works on quadruped manipulators, the MPC is directly interfaced with the low-level joint impedance controllers without the need of designing an instantaneous whole-body controller. The feasibility on the real hardware is showcased using the CENTAURO platform for the challenging task of picking a heavy object from the ground. Dynamic stepping (trotting) is also showcased for first time with this robot. The results highlight the potential of replanning with whole-body information in a predictive control loop. Copyright © 2023, The Authors. All rights reserved.

关键词： Model predictive control

Lower Leg Joint Strategies in the Outside Pass in Soccer

学校读者我要写书评

暂无评论

Lower Leg Joint Strategies in the Outside Pass in Soccer

18th International Joint Conference on Biomedical engineering systems and Technologies, BIOSTEC 2025

作者： Yamamoto, Yudai Kozák, Viktor Mizuuchi, Ikuo Department of Food and Energy Systems Science Tokyo University of Agriculture and Technology Naka-cho 2-24-16 Koganei-shi Tokyo-to184-0012 Japan Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Jugoslávských Partyzánú 1580/3 Praha 6160 00 Czech Republic Department of Mechanical Systems Engineering Tokyo University of Agriculture and Technology Naka-cho 2-24-16 Koganei-shi Tokyo-to184-0012 Japan

Westudy the leg motion for an outside pass in soccer, observing four different movement strategies. The aim of this research is to validate the presence of these four strategies by training an agent with a higher reward for kicking a faster ball. Additionally, we aim to explore the role of the collateral ligaments’ stiffness in the outside pass. We built two leg models: (a) a two-degree-of-freedom leg model that applies torque around the hip joint, and (b) a three-degree-freedom leg model that applies pitch-roll-yaw torque around the hip joint and pitch torque around the knee joint. We trained a Deep Deterministic Policy Gradient (DDPG) agent using these models and analyzed the torques around the hip and knee joints, as well as the ball velocity after the leg loses contact with the ball. We observed three strategies similar to human behavior throughout agent learning. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Degrees of freedom (mechanics)

Optimal camera-robot pose estimation in linear time from points and lines

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Zeng, Guangyang Mu, Biqiang Zeng, Qingcheng Song, Yuchen Dai, Chulin Shi, Guodong Wu, Junfeng School of Data Science Chinese University of Hong Kong Shenzhen China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Guangzhou China Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Sydney Australia

Camera pose estimation is a fundamental problem in robotics. This paper focuses on two issues of interest: First, point and line features have complementary advantages, and it is of great value to design a uniform algorithm that can fuse them effectively;Second, with the development of modern front-end techniques, a large number of features can exist in a single image, which presents a potential for highly accurate robot pose estimation. With these observations, we propose AOPnP(L), an optimal linear-time camera-robot pose estimation algorithm from points and lines. Specifically, we represent a line with two distinct points on it and unify the noise model for point and line measurements where noises are added to 2D points in the image. By utilizing Plücker coordinates for line parameterization, we formulate a maximum likelihood (ML) problem for combined point and line measurements. To optimally solve the ML problem, AOPnP(L) adopts a two-step estimation scheme. In the first step, a consistent estimate that can converge to the true pose is devised by virtue of bias elimination. In the second step, a single Gauss-Newton iteration is executed to refine the initial estimate. AOPnP(L) features theoretical optimality in the sense that its mean squared error converges to the Cramér-Rao lower bound. Moreover, it owns a linear time complexity. These properties make it well-suited for precision-demanding and real-time robot pose estimation. Extensive experiments are conducted to validate our theoretical developments and demonstrate the superiority of AOPnP(L) in both static localization and dynamic odometry systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Mean square error

Vision-Based Normalized Canopy Area Estimation for Variable Nitrogen Application in Apple Orchards

学校读者我要写书评

暂无评论

SSRN

SSRN 2023年

作者： Paudel, Achyut Karkee, Manoj Davidson, Joseph R. Grimm, Cindy Biological Systems Engineering Department Center for Precision and Automated Agricultural System Washington State University ProsserWA99350 United States Collaborative Robotics and Intelligent Systems Institute Oregon State University CorvallisOR97331 United States

Normalized canopy area is a measure of spatial canopy fill or canopy coverage in a tree. It is an important factor for growers to consider in making various farming decisions, such as timing and amount of fertilization, pesticide application, and irrigation, as it gives a sense of the overall canopy growth. This study focused on estimating the normalized canopy area of apple trees using a ground-based stereo-vision system in a commercial orchard under natural lighting conditions. A color, depth, and height threshold, followed by a point density-based outlier removal was applied to segment the target tree canopies. The segmented canopy area was compared with the area estimated with manual segmentation, which showed an F1 score of 0.78. The overall growth of the tree canopies was then represented using normalized canopy area, which was calculated as a fraction of pixels occupied by the tree foliage over the total possible area a tree could occupy for a given tree spacing. It was found that the normalized canopy area of individual trees was highly correlated with the surface volume of the canopy (r = 0.7), which is a traditionally used parameter to assess or represent canopy growth. The estimated normalized canopy area was then compared against experts’ nitrogen recommendation for the sample trees, which was based on their visual assessment of the vigor/growth of the trees. Four individual experts (one apple farmer, one orchard manager, and two horticulturists with research and outreach experience) were asked to provide their independent nitrogen recommendation and an average recommendation level was calculated. The comparison showed an overall correlation coefficient of - 0.5, indicating an opposite relationship (higher the canopy density, lower the need for nitrogen and vice versa) between the normalized canopy area and the average of the experts’ nitrogen recommendation. When the relationship between the normalized area and nitrogen recommendation level was assessed

关键词： Orchards

Periodic Proprioceptive Stimuli Learning and Internal Model Development for Avian-inspired Flapping-wing Flight State Estimation

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Qian, Chen Xing, Jiaxi Yan, Jifu Luo, Mingyu Song, Shiyu Lian, Xuyi Fang, Yongchun Gao, Fei Li, Tiefeng Center for X-mechanics of Zhejiang University China Huzhou Institute of Zhejiang University China Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Nankai University China School of Mechanical Engineering Zhejiang University China School of Aeronautics and Astronautics Zhejiang University China College of Control Science and Engineering Zhejiang University China

This paper presents a novel learning-based approach for online state estimation in flapping wing aerial vehicles (FWAVs). Leveraging low-cost Magnetic, Angular Rate, and Gravity (MARG) sensors, the proposed method effectively mitigates the adverse effects of flapping-induced oscillations that challenge conventional estimation techniques. By employing a divide-and-conquer strategy grounded in cycle-averaged aerodynamics, the framework decouples the slow-varying components from the high-frequency oscillatory components, thereby preserving critical transient behaviors while delivering an smooth internal state representation. The complete oscillatory state of FWAV can be reconstructed based on above two components, leading to substantial improvements in accurate state prediction. Experimental validations on an avian-inspired FWAV demonstrate that the estimator enhances accuracy and smoothness, even under complex aerodynamic disturbances. These encouraging results highlight the potential of learning algorithms to overcome issues of flapping-wing induced oscillation dynamics. Copyright © 2025, The Authors. All rights reserved.

关键词： Magnetic levitation vehicles

Design and analysis of a soft bellow-based robot for dysphagia rehabilitation 30

学校读者我要写书评

暂无评论

Design and analysis of a soft bellow-based robot for dysphag...

30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Guo, Linlin Dang, Yu Wang, Yue Wu, Jinqiao Yu, Yang Wu, Jialing Han, Jianda College of Artificial Intelligence Nankai University Tianjin300350 China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute Nankai University Shenzhen518083 China Department of Rehabilitation Medicine Tianjin Huanhu Hospital Tianjin300350 China Department of Neurology Tianjin Huanhu Hospital Tianjin300350 China

ISBN: (纸本)9798350391916

As the population ages, the incidence of diseases such as stroke is increasing, leading to a growing number of patients with dysphagia or difficulty swallowing. Dysphagia directly affects the hydration and nutritional intake, potentially leading to serious complications such as aspiration pneumonia, severely threatening patients' health and quality of life. Currently, the rehabilitation of swallowing function mainly relies on therapists to conduct swallowing training for patients. However, the high incidence and long duration of swallowing rehabilitation training pose a burden on the patients and medical resources. There remains a gap in the robotic devices for swallowing rehabilitation. To address this gap, this paper proposes a soft bellow-shaped robot for dysphagia rehabilitation. One mode of the rehabilitation training, where the therapist manipulates the throat to move horizontally, is selected to mimic. This robot simulates the force and displacement applied by the therapist's fingertip during dysphagia rehabilitation. First, swallowing training data were collected and analyzed to understand the variations in displacement and force applied by therapists' fingertips on the throat. Based on this analysis, the technical requirements for the swallowing rehabilitation robot were summarized. Following these requirements, we designed a physical prototype of the pneumatic bellow-shaped robot. The robot simulates the fingertip movement on both sides of the throat through the linear elongation and contraction of the bellows. The performance of the soft bellows was then characterized, verifying that its output force and displacement meet the technical requirements. This characterization lays a foundation for the modeling and control of the displacement and force of the robot. © 2024 IEEE.

关键词： Bellows