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7th International Conference on Cognitive systems and Information Processing, ICCSIP 2022

作者： Zhou, Huaidong Tuo, Wanchen Chou, Wusheng Robotics Institute School of Mechanical Engineering and Automation Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China

ISBN: (纸本)9789819906161

Robot location is a fundamental technology in the field of autonomous robotics and has been widely studied. However, high-precision localization of the mobile robot is still a serious challenge. To investigate this point further, this paper proposes a method to improve the autonomous robot localization accuracy, which adjusts the number of particles in the AMCL algorithm by fusing the information of LRL. LRL data is used to improve the localization accuracy of mobile platforms and prevent kidnapped robot problems. The algorithm is conducted and verified in a real robot system. The experiment results show that the proposed method can achieve high-precision locations in real-world scenarios, and verify the effectiveness of the improved localization system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mobile robots

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Human-in-the-loop Optimization for Adaptive Assist-as-Needed Rehabilitation 12

Human-in-the-loop Optimization for Adaptive Assist-as-Needed...

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12th International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Li, Ning Yang, Yang Yang, Tie Chen, Wenyuan Wang, Yihan Yu, Peng Wang, Wenxue Xi, Ning Liu, Lianqing Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of the Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang10016 China School of Electrical and Electronics Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Emerging Technologies Institute Department of Industrial and Manufacturing Systems Engineering University of Hong Kong Pokfulam999077 Hong Kong

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Active voluntary participation in robot-assisted rehabilitation promote the recovery of stroke hemiplegia. However, different patients have personalized recovery states, which needs the adaptive control strategy to improve the patient's participation. Therefore, in this study, a Mirror Adaptive Assist-As-Needed (MAAN) scheme is proposed to encourage subjects to participate actively and avoid the slack of the subjects including two modules: Functional Capability Estimation (FCE) and Mirror Adaptation (MAD). Specifically, the first MSFE module can obtain joint functional capability based on fused biological and motional signals. The second MAD module acquires the needed assistance via the estimated torques of FCE based on healthy limb. Through the iteration and collaboration of these two modules, a human-in-the-loop adaptive training is achieved to promote the patient participation. The results demonstrate that the MAAN strategy can generate suitable assistance for the patients to correct abnormal muscle activation patterns and promote active voluntary participation. Compared with other methods, the proposed strategy improves motion stability and consistency with the natural physiological state of healthy limbs. This research can be expected to greatly enhance the rehabilitation and power assistance outcome of exoskeleton robot in more practical applications. © 2022 IEEE.

关键词： Mirrors

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

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

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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

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Dynamic Setpoint Optimization Using Metaheuristic Algorithms for Wastewater Treatment Plants 48

Dynamic Setpoint Optimization Using Metaheuristic Algorithms...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Salles, Rodrigo Mendes, Jerome Henggeler Antunes, Carlos Moura, Pedro Dias, Joana University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Pólo II Coimbra3030-290 Portugal University of Coimbra Inesc Coimbra Department of Electrical and Computer Engineering Pólo II Coimbra3030-290 Portugal Ctga Park no 70 Taveiro Coimbra3045-487 Portugal

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Wastewater Treatment Plants (WWTPs) are complex structures, with nonlinear characteristics, that have strict quality criteria, and carry out the treatment using various resources, with special emphasis on electricity. The optimization of WWTPs is a necessity to achieve sustainability. This work proposes the use of metaheuristic algorithms to optimize the functioning of a WWTP. Genetic Algorithm, Particle Swarm Optimization, and Simulated Annealing are used to minimize the aeration energy consumption prediction by an artificial neural network. The optimization framework aims dynamically adjusts the reference value for the proportional-integral (PI) controller. The proposed approach was able to dynamically adjust the oxygen pumping requirement and thus reduce the electricity consumption compared to the default PI controller adopted by the Benchmark Simulation Model no. 2 (BSM2). © 2022 IEEE.

关键词： Genetic algorithms

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

arXiv

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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

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Design and Dynamic Locomotion Control of Quadruped Robot with Perception-Less Terrain Adaptation

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Cyborg and Bionic systems 2022年第1期2022卷 177-186页

作者： Lei Wang Libo Meng Ru Kang Botao Liu Sai Gu Zhihao Zhang Fei Meng Aiguo Ming Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of TechnologyBejing 100081China Beijing Advanced Imnovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Department of Mechanical Engineering and Itelligent Systerms The University of Electro-CommunicationsTokyo 182-8585Japan

In this paper,a parallel quadrupedal robot was designed that is capable of versatile dynamic locomotion and perception-less terrain ***,a quadrupedal robot with a symmetric legs and a powerful actuator was implemented for highly dynamic ***,a fast and reliable method based on generalized least square was proposed for estimating the terrain parameters by fusing the body,leg,and contact *** the basis of virtual model control(VMC)with the quadratic program(QP)method,the optimal foot force for terrain adaptation was ***,the results obtained by simulation and indoor and outdoor experiments demonstrate that the robot can achieve a robust and versa tile dynamic locomotion on uneven terrain,and the rejection of disturbances is reliable,which proves the effectiveness and robustness of this proposed method.

关键词： robot Robot terrain

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Lower Leg Joint Strategies in the Outside Pass in Soccer

Lower Leg Joint Strategies in the Outside Pass in Soccer

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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)

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FDNet: Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Fourier Series and DenseNet

FDNet: Remaining Useful Life Prediction for Lithium-Ion Batt...

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Machine Learning and Computer Application (ICMLCA), International Conference on

作者： Siwen Chen Xiujuan Zheng Shanghai United Imaging Healthcare Co. Ltd Shanghai China Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

To enhance the prediction accuracy of the remaining useful life (RUL) of lithium-ion batteries, this study proposes a novel RUL prediction model, termed FDNet, which integrates Discrete Fourier Series (DFS) and Densely Connected Convolutional Networks (DenseNet). In contrast to traditional methods that rely on one-dimensional (1D) numerical representations of time-series data, this model utilizes a two-dimensional (2D) visual representation for direct RUL prediction. First, the DFS is employed to convert 1D time-series signals into a 2D time-frequency domain, enabling the extraction of high-dimensional features from the original data. Then, these 2D images are subsequently input into DenseNet, which learns the mapping between the image features and the RUL targets. Finally, the proposed model is validated using the NASA lithium-ion battery aging dataset, and the results indicate that FDNet achieves superior prediction accuracy and exhibits notable robustness.

关键词： Lithium-ion batteries Time-frequency analysis Accuracy NASA Predictive models Feature extraction Robustness Numerical models Fourier series Convolutional neural networks

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

arXiv

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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

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From Conventional Non-Conductive Foams to Soft Piezoresistive Pressure Sensors: A Low-Cost Approach to Large-Area Pressure-Mapping

From Conventional Non-Conductive Foams to Soft Piezoresistiv...

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IEEE SENSORS

作者： Manuel Reis Carneiro Luis Rosa Mahmoud Tavakoli Dept. of Electrical and Comp. Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal Dept. of Mechanical Engineering Soft Machines Lab Carnegie Mellon University Pittsburgh Pennsylvania United States

This article presents a low-cost, and scalable method for synthesizing large sheets of functionalized foam for soft resistive pressure sensing that is compatible with any commercially available non-conductive foam. The process is illustrated by soaking Pu (Polyurethane) foam in a carbon-based polymeric mixture resulting in a functional foam with large pressure detection range up to 500 kPa, while retaining its deformability and recoverability after cyclic compression. The foam also shows unprecedentedly fast response time of ~120 ms. The foam was integrated in a wearable respiration sensor and in a large multitouch sensing mat that allows for precise data acquisition on the position and intensity of various simultaneous touches without the occurrence of ghost touches.

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