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42nd Chinese Control Conference, CCC 2023

作者： Sun, Yubo Guo, Zhenhui Feng, Yuxin Yu, Ningbo College of Artificial Intelligence Nankai University Tianjin300350 China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute Nankai University Shenzhen518083 China

ISBN: (纸本)9789887581543

Surface electromyography (sEMG) is a non-invasive technique for recording electrical activity and is extensively employed in gait phase classification. However, the measurement process of the sEMG signal inevitably introduces noise. Consequently, denoising is required for gait analysis from the collected sEMG signal. A novel denoising method ICEEMDAN-DFA-WD has been proposed in this paper. The sEMG signals were decomposed into several intrinsic mode functions (IMF) through an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN). The Hurst exponents were simulated by detrended fluctuation analysis (DFA) to distinguish noisy IMF and desired IMF. During the walking process, the lower limbs' sEMG exhibits strong periodicity, and the desired IMF yields higher Hurst exponents than the noisy IMF. For the noisy IMF, noise removal was performed through further decomposition by wavelet transform, followed by a hard threshold. The processed IMFs were reconstructed to denoise sEMG. In this study, experiments were conducted to compare with the existing denoising methods WD, EMD-IIT, EEMD-IWT, VMD-SIT. The proposed method can obtain better denoising effect and gait phase classification accuracy. The proposed method provides a more effective way for sEMG denoising. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Empirical mode decomposition

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Modelling and Control of a Trailer Sprayer for Precision Spraying

Modelling and Control of a Trailer Sprayer for Precision Spr...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： André Baltazar Filipe N. Santos Antόnio Paulo Moreira Salviano Pinto Soares M. J. C. S. Reis José Boaventura Cunha CRIIS-Centre for Robotics in Industry and Intelligent Systems INESC TEC—Institute for Systems and Computer Engineering Technology and Science Porto Portugal ECT—School of Science and Technology UTAD—University of Trás-os-Montes and Alto Douro Vila Real Portugal FEUP—Faculty of Engineering University of Porto Porto Portugal Institute of Electronics and Informatics Engineering of Aveiro (IEETA) Portugal Intelligent Systems Associate Laboratory (LASI) Portugal

ISBN: (数字)9798350352344

ISBN: (纸本)9798350352351

Precision spraying in agriculture is crucial for optimizing the application of pesticides while minimizing environmental impact. Despite significant advancements in control models for spraying systems, predictive control algorithms were not used. This paper addresses this gap by proposing a real-time control framework that integrates predictive control strategies to ensure consistent pressure output in a trailer sprayer. Based on information from various sensors, the framework anticipates and adapts to dynamic environmental conditions, enhancing accuracy and sustainability in spraying practices. A methodology is developed to define a proportional valve model. Based on this valve model, the predictive control model optimizes valve movements to minimize errors between predicted and reference pressures, thereby improving spraying efficiency. This study demonstrates the viability of predictive control in improving precision spraying systems applicable to autonomous robots, encouraging future advances in agricultural spraying technologies.

关键词： Adaptation models Spraying Predictive models Valves Real-time systems Agriculture Sensors

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A Robust Surveillance System for AGV Using Forward-Downward Visual Measurements

A Robust Surveillance System for AGV Using Forward-Downward ...

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Chinese Control and Decision Conference, CCDC

作者： Sichao Zhang Wei Liang Xudong Yuan Haibo An Meng Zheng Yinlong Zhang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Science and Technology on Information Systems Engineering Laboratory the 28th Research Institute of CETC Nanjing China

Automatic Guided Vehicle (AGV) has been widely used in the warehouse for transporting the bulky and heavy cargos. However, the AGV may deviate the regular trajectories in presence of incorrect or untimely commands sent form the server due to, e.g., cyber attacks, unexpected blocks of the wireless signals. In order to ensure AGV running safely, this paper presents a visual surveillance system by making full use of the measurements from the forward and downward cameras. Specifically, the forward camera estimates the AGV positions and attitudes by tracking the surrounding landmarks detected from the forward image sequences. Besides, the downward camera is used to detect the QR codes fixed on the floor and estimate the AGV poses in the absolute reference frame. Apart from that, the AGV poses from the downward camera could correct scale and poses estimated the forward view. The proposed method has been extensively performed on the developed platform. The results proves the effectiveness in using the complementary forward-downward visual measurements for AGV security surveillance.

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Research on Multiple Automated Guided Vehicles Path Planning to Reduce Default Time 2

Research on Multiple Automated Guided Vehicles Path Planning...

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2nd IEEE International Conference on Data Science and Computer Application, ICDSCA 2022

作者： Liu, Yiyang Yan, Shuaihua Hou, Zheng Zhao, Yang Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China Kunshan Intelligent Equipment Research Institute Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China University of Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China College of Information Science and Engineering Northeastern University Shenyang China School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

This paper studies the path planning problem of multiple automated guided vehicles (multi-AGV) in a matrix manufacturing workshop. We proposed the multi-AGV path planning problem with default time, which is a variant of the classic path planning problem. In order to ensure the timely completion of each task, the default time of the task is explicitly considered. The goal is to obtain a conflict-free path with the minimum total default time, total time, and total path length. For these three goals, this problem is NP-hard. In order to solve this problem better, we established a multi-objective optimization model of total default time, total time and total path length of multi-AGV in flexible manufacturing environment. This paper proposes a multi-AGV path planning method that integrates game theory and A∗ algorithm. This method regards each AGV as a participant in the game model, through the default time obtained from each game dynamically adjusts the probability of each AGV planning the next path, and uses game theory to help the system dynamically select the most suitable AGV to plan the next path to improve the on-time delivery rate of tasks. Finally, the simulation results show that the multi-AGV path planning method integrating game theory and A∗ algorithm further reduces the total default time, total time and total path length of all AGVs. © 2022 IEEE.

关键词： Motion planning

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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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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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Design and Research on a Vision-based Lightweight Soft Ankle Exosuit 8

Design and Research on a Vision-based Lightweight Soft Ankle...

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8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Bao, Bingsheng Tu, Yao Dang, Diyang Zhu, Aibin Wang, Xin Zhou, Xu Gao, Chong Zhang, Zheng Xu, Haibo Institute of Robotics & Intelligent Systems Xi'An Jiaotong University Shaanxi Key Laboratory of Intelligent Robots Xi'an710049 China Xi'An Jiaotong University Xi'an710049 China School of Construction Machinery Chang'An University Xi'an710064 China School of Mechanical Engineering Northwestern Polytechnical University Xi'an710072 China Taiyuan Research Institute of China Coal Technology & Engineering Group Co. Ltd Taiyuan030006 China

ISBN: (纸本)9798350300178

There has been growing interest in the development of exosuit-assisted locomotion to effectively assist human motion. In this study, we present a novel soft ankle joint exosuit capable of providing dynamic support in varying terrains. The exosuit's underdriven structural design, combined with the use of visual sensors for real-time environmental detection, distinguishes it from existing solutions. The underdriven design enables the exosuit to achieve two degrees of freedom using a single actuator, thus improving its mobility and functionality. Additionally, we employ a semantic segmentation model based on deep learning to recognize the terrain of the environment and adapt the exosuit's assistance accordingly. The visual sensors provide real-time information to the system, allowing it to switch between assisted states and improve the exosuit's overall performance. We carried out experiments on a prototype to validate our proposed approach. With 83% accuracy of terrain recognition, the results demonstrate its feasibility and potential for future development. © 2023 IEEE.

关键词： Structural design

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NBV-HRR: Next Best View Planning Network for Highly Reflective Region Restoration in Robotic 3-D Scanning

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IEEE/ASME Transactions on Mechatronics 2024年

作者： Ouyang, Jun Liu, Daohui Jia, Peng Liu, Xinyu Liu, Xingjian Sun, Yu Dalian University of Technology Institute of Robotics and Intelligent Systems the State Key Laboratory of High-Performance Precision Manufacturing Dalian116024 China University of Toronto Department of Mechanical and Industrial Engineering TorontoONM5S 3G8 Canada

Three-dimensional scanning of highly reflective surfaces is a challenge faced in industrial metrology. The high dynamic range (HDR) technique offers a solution by fusing images taken at various exposures. However, its effectiveness is limited in regions where reflectivity exceeds the camera's dynamic range. To address this issue, this article introduces a next best view (NBV) planning network for the restoration of highly reflective regions, named NBV-HRR. Unlike traditional NBV networks focused on complete shape reconstruction utilizing global features, NBV-HRR targets the restoration of localized regions lost due to reflection, utilizing both global and local features. To accurately evaluate each view, a cross-attention-based module is devised to fuse features of varying dimensions. For network training, a dataset containing 70 400 training samples was collected from over 1000 highly reflective industrial parts in both simulation and real scenes. Experimental results demonstrated that the proposed NBV-HRR network achieved an average restoration rate of 99.3% within three NBV predictions, significantly outperforming the HDR technique (83.7%). © 2024 IEEE.

关键词： Restoration

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A Bipedal Wheel-Legged Robot with High-frequency Force Control by Qausi-Direct Drive: Design and Experiments

A Bipedal Wheel-Legged Robot with High-frequency Force Contr...

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IEEE International Conference on robotics and Biomimetics

作者： Yuntian Zhao Shiyuan Lin Zheng Zhu Zhenzhong Jia Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology (SUSTech) Shenzhen China

ISBN: (纸本)9781665481106

Under-actuated systems like bipedal wheel-legged robots have dynamics coupled with force control, which cannot be separated or integrated out. Joint force control is necessary for these robots to realize model based controllers. In this paper, we design a bipedal wheel-legged robot prototype with proprioceptive quasi-direct drive (QDD) actuators to realize high-frequency force control and good back-drivability to deal with unexpected impacts. We compare the control bandwidth, back-drivability (impact mitigation capability) of three commonly used force-control actuation paradigms including geareddown motor with integrated torque sensor, QDD, and SEA (series elastic actuation) in details. Detailed actuator calibration reveals good current-torque linearity, thereby simplifying the control problem. We also use EtherCAT-based communication network and real-time main controller to ensure high control frequency. We derive the robot dynamics model, establish the simulation model, and design a LQR controller, in order to demonstrate our proposed design. Moreover, in the real-world experiments, we use a velocity-based balance controller together with position joint controller to show preliminary mobility, including balancing, rotating, and forward motion.

关键词： Actuators Torque Dynamics Prototypes Propioception Linearity Real-time systems

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Techno-Economic Assessment of a Large-Scale Electrolysis Plant in Hydrogen and Ancillary Service Markets

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IFAC-PapersOnLine 2024年第13期58卷 140-145页

作者： Yassine Ennassiri Giulio Ferro Michela Robba Gilney Damm Edemar O. Prado DIBRIS—Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova 16145 Italy IMSE Laboratory Gustave Eiffel University Marne-la-Vallée France Power Electronics and Control Research Group GEPOC Federal University of Santa Maria SantaMaria 97105-900 RS Brazil

Hydrogen electrolysis systems have seen considerable interest from energy communities as a potential solution for shifting from fossil-based energy resources to clean energy alternatives. The system consists of transforming electricity into hydrogen via water electrolysis. As it is expected to have a large-scale connection with the grid to compensate the fluctuation of renewables, it is important to understand the system’s technical and economic feasibility. Therefore, this work aims to provide a high-level techno-economic assessment for the participation of a large-scale electrolysis plant in hydrogen and grid ancillary service markets. The plant generates revenue from two sources: hydrogen and frequency regulation. Based on market prices of electricity and hydrogen, a linear programming (LP) optimization has shown that a 50MW electrolysis plant can generate a 33% increase in profit if the plant includes the grid support market in the business model. Additionally, simulations under unstable grid frequency have shown high reactivity of the system to maintain grid stability.

关键词： optimization hydrogen production frequency regulation linear programming

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