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Annual Conference of Industrial Electronics Society

作者： Linya Fu Xu Qiao Shoudong Huang Guoqiang Mao Zhiyun Lin Youfu Li He Kong Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern Uni. of Sci. and Tech. Shenzhen China Robotics Institute Uni. of Technology Sydney Sydney Australia State Key Laboratory of Integrated Services Networks Xidian University China Department of Mechanical Engineering City University of Hong Kong China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern Uni. of Sci. and Tech. Shenzhen China

Sensor arrays generating differential received signal strength (DRSS) measurements have found many applications in robotics. However, accurate calibration of these sensor arrays remains a challenge. Most existing methods are impractical in that they assume to know signal source positions or certain parameters (i.e., path loss exponent), and try to estimate the others. In this paper, we adopt graph simultaneous localization and mapping (SLAM) as a general framework for jointly estimating the source positions and parameters of the DRSS sensor array. Our contributions are twofold. On the one hand, by using a Fisher information matrix approach, we conduct a systematic observability analysis of the corresponding SLAM setup for the calibration problem. On the other hand, we propose an effective procedure to select the initial value which is fed to Levenberg-Marquardt iterations for further improving optimization accuracy and convergence. Extensive simulation and hardware experiments show that the proposed method renders high-quality calibration results. All the codes and data are publicly available at https://***/SUSTech2022/DRSS-sensor-array-calibration.

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Visual-Inertial and Leg Odometry Fusion for Dynamic Locomotion

arXiv

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arXiv 2022年

作者： Dhédin, Victor Li, Haolong Khorshidi, Shahram Mack, Lukas Ravi, Adithya Kumar Chinnakkonda Meduri, Avadesh Shah, Paarth Grimminger, Felix Righetti, Ludovic Khadiv, Majid Stueckler, Joerg Embodied Vision Group Max Planck Institute for Intelligent Systems Tuebingen Germany Movement Generation and Control Group Max Planck Institute for Intelligent Systems Tuebingen Germany Tandon School of Engineering New York University New York United States Oxford Robotics Institute University of Oxford United Kingdom Autonomous Motion Department Max Planck Institute for Intelligent Systems Tuebingen Germany

Implementing dynamic locomotion behaviors on legged robots requires a high-quality state estimation module. Especially when the motion includes flight phases, state-of-the-art approaches fail to produce reliable estimation of the robot posture, in particular base height. In this paper, we propose a novel approach for combining visual-inertial odometry (VIO) with leg odometry in an extended Kalman filter (EKF) based state estimator. The VIO module uses a stereo camera and IMU to yield low-drift 3D position and yaw orientation and drift-free pitch and roll orientation of the robot base link in the inertial frame. However, these values have a considerable amount of latency due to image processing and optimization, while the rate of update is quite low which is not suitable for low-level control. To reduce the latency, we predict the VIO state estimate at the rate of the IMU measurements of the VIO sensor. The EKF module uses the base pose and linear velocity predicted by VIO, fuses them further with a second high-rate IMU and leg odometry measurements, and produces robot state estimates with a high frequency and small latency suitable for control. We integrate this lightweight estimation framework with a nonlinear model predictive controller and show successful implementation of a set of agile locomotion behaviors, including trotting and jumping at varying horizontal speeds, on a torque-controlled quadruped robot. Copyright © 2022, The Authors. All rights reserved.

关键词： Extended Kalman filters

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Admittance control Based Gait Intervention Strategy of Knee Exoskeleton for Stance Phase Support

Admittance Control Based Gait Intervention Strategy of Knee ...

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IEEE/ASME (AIM) International Conference on Advanced intelligent Mechatronics

作者： Xiaolin Dai Zhihao Zhou Zilu Wang Xuewen Rong Qining Wang School of Control Science and Engineering Shandong University Jinan China University of Health and Rehabilitation Sciences Qingdao China Institute for Artificial Intelligence Peking University Beijing China Beijing Engineering Research Center of Intelligent Rehabilitation Engineering Beijing China College of Engineering Peking University Beijing China School of Control Science and Engineering Shandong University and Engineering Research Center of Intelligent Un-manned System of Ministry of Education Jinan China Department of Advanced Manufacturing and Robotics College of Engineering with the Institute for Artificial Intelligence Peking University Beijing China Peking University Third Hospital Beijing China Fifth Affiliated Hospital of Zhengzhou University Henan China

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Knee exoskeletons have been utilized for gait rehabilitation in patients after total knee arthroplasty. During the early and middle stance phases of walking gaits, the knee joint activity of these patients is either absent or reduced, which is not conducive to the rehabilitation of normal gaits. Currently, most exoskeletons used for the rehabilitation of patients after TKA correct gait by pre-setting the movement trajectory of the knee joint. However, this method faces challenges in terms of human-machine interaction and safety. This paper proposes a strategy that combines admittance control during the early and middle stance phases with position control during the late stance and swing phases to improve compliance and safety between the wearer and the knee exoskeleton. The exoskeleton can provide support to the knee joint during the early and middle stance phases according to the wearer’s actual movement requirements. The performance and safety of the admittance control were verified through test bench and squat-to-stand experiments, while the gait intervention strategy was validated through a downhill walking experiment.

关键词： Knee Legged locomotion Torque Mechatronics Exoskeletons Position control Safety

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Volume-based Transition Zone Assessment of Hybrid Unmanned Aerial-Underwater Vehicles

Volume-based Transition Zone Assessment of Hybrid Unmanned A...

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IEEE Latin American robotics Symposium, LARS

作者： Vivian Misaki Aoki Paulo Jefferson Dias De Oliveira Evald Pedro Miranda Pinheiro César Bastos Da Silva Dayana Dos Santos Cardoso Mauro André Barbosa Cunha Paulo Lilles Jorge Drews Intelligent Robotics and Automation Group Federal University of Rio Grande Rio Grande Brazil Department of Computer Engineering and Industrial Automation State University of Campinas Campinas Brazil Automation and Control Research Group Sul-rio-grandense Federal Institute Pelotas Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

Quadrotors have been used in diverse areas, such as agriculture, civil construction, fire monitoring, and so on. However, these vehicles cannot perform missions that require navigation in aquatic environments, such as inspection of underwater structures and water sample collection, due to their hardware limitations. Therefore, hybrid unmanned aerial-underwater vehicles emerge as a feasible solution to accomplish these missions. Although quadrotors have well-accepted mathematical models, hybrid vehicles have a small quantity of works dealing with this topic. Moreover, we identified a gap in transition zone representation. Therefore, this paper presents a method for transition zone modeling based on vehicle geometry. Simulation results support the better representation of the proposed transition model in comparison to a sigmoid model.

关键词： Underwater structures Navigation Simulation Force Inspection Mathematical models Hardware

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Riemannian Online Optimistic Algorithms with Dynamic Regret

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IEEE Transactions on Automatic control 2025年

作者： Wang, Xi Yuan, Deming Hong, Yiguang Hu, Zihao Wang, Lei Shi, Guodong University of New South Wales School of Electrical Engineering & Telecommunications SydneyNSW2052 Australia Nanjing University of Science and Technology School of Automation Nanjing210094 China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Hong Kong University of Science and Technology Department of Mathematics Hong Kong Zhejiang University College of Control Science and Engineering Zhejiang 310058 China The University of Sydney Australian Center for Robotics School of Aerospace Mechanical and Mechatronic Engineering NSW2006 Australia

In this paper, we consider Riemannian online convex optimization with dynamic regret, which involves minimizing the cumulative loss difference between a learner's decisions and a sequence of adaptive decisions across dynamic environments over time on Riemannian manifolds. First, we propose Riemannian Online Optimistic Gradient Descent (R-OOGD), which extends the classical optimistic algorithms to Riemannian manifolds, requiring one gradient inquiry per round. We then propose Riemannian Adaptive Online Optimistic Gradient Descent (R-AOOGD) by incorporating the meta-expert framework into R-OOGD. We analyze the dynamic regret of R-OOGD and R-AOOGD in terms of the regularity of the sequence of cost functions and comparators. The dynamic regret bound matches the results in Euclidean space and with a scale adjustment of O(1+κ D2/√1-KD2) related to the sectional curvature lower bound κ, sectional curvature upper bound and feasible set diameter. Finally, we provide numerical experiments to illustrate the performance of the proposed algorithms. © 1963-2012 IEEE.

关键词： Optimization algorithms

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A Review on Collaborative Robots in Industrial and Service Sectors

A Review on Collaborative Robots in Industrial and Service S...

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Siberian Conference on control and Communications (SIBCON)

作者： Ramir Sultanov Shifa Sulaiman Hongbing Li Roman Meshcheryakov Evgeni Magid Intelligent Robotics Department Kazan Federal University Kazan Russia Department of Instrument Science and Engineering Shanghai Jiao Tong University Shanghai China Cyber-physical Lab V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia HSE University Moscow Russia

ISBN: (纸本)9781665476294

Today, a collaborative robotics is a rapidly developing area due to its applications in a broad variety of sectors. Collaborative robots (cobots) are robots, which are designed specifically to work along with humans in a common workspace. This article discusses modern cobots employed in industrial and service sectors. Research activities associated with cobots used in virtual environments and real world experiments are described. The ISO/TS 15066:2016 technical specifications followed by cobots for ensuring safety to human operators are emphasized.

关键词： Learning systems Service robots Collaboration Virtual environments Process control Human-robot interaction Production

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Joint Routing and Charging Problem of Electric Vehicles with Incentive-Aware Customers Considering Spatio-Temporal Charging Prices

SSRN

引用

SSRN 2022年

作者： Yao, Canqi Chen, Shibo Salazar, Mauro Yang, Zaiyue School of Mechatronics Engineering Harbin Institute of Technology Harbin150000 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering The Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology EindhovenMB 5600 Netherlands

This paper investigates the scheduling problem of a fleet of electric vehicles, providing mobility as a service to a set of time-specified customers, where the operator needs to solve the routing and charging problem jointly for each EV. Hereby we consider incentive-aware customers and propose that the operator offers monetary incentives to customers in exchange for time flexibility. In this way, the fleet operator can achieve a routing and charging schedule with lower costs, whilst the customers receive monetary compensation for their flexibility. Specifically, we first propose a bi-level optimization model whereby the fleet operator optimizes the routing and charging schedule accounting for the spatio-temporal varying charging price, jointly with a monetary incentive to reimburse the delivery time flexibility experienced by the customers. Concurrently the customers choose their own time flexibility by minimizing their own cost. Second, we cope with the computational burden coming from this nonlinear bi-level optimization model with an accurate reformulation approach consisting of the KKT optimality conditions, a Big-M-based linearization method, and the zero duality gap of convex optimization problems. This way, we convert the proposed problem into a single-level optimization problem, which can be solved by a strengthened generalized Benders decomposition method holding a faster convergence rate than the generalized Benders decomposition method. To evaluate the effectiveness of the proposed mathematical model, we carry out numerous simulation experiments by using the VRP-REP data of Belgium. The numerical results showcase that the proposed mathematical model can reduce the delivery fees for the customers together with the cost of operation incurred by the fleet operator. © 2022, The Authors. All rights reserved.

关键词： Sales

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Joint Routing and Charging Problem of Electric Vehicles with Incentive-aware Customers Considering Spatio-temporal Charging Prices

arXiv

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arXiv 2022年

关键词： Sales

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AGV Semantic Attack Detection Based on Hidden Markov Model

AGV Semantic Attack Detection Based on Hidden Markov Model

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IEEE International Conference on Industrial Technology (ICIT)

作者： Sichao Zhang Wei Liang Yinlong Zhang Zhibo Pang 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 Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Department of Automation Technology ABB Corporate Research Sweden Vasteras Sweden

ISBN: (纸本)9781728119496

Automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, because of the unexpected wireless radio frequency interference. This paper investigates a new method for AGV semantic attack detection based on Hidden Markov Model (HMM). Our method is able to discriminate the typical wireless retransmission in presence of environment interference or in the context of AGV semantic attack by comparing the hidden state transition probability with the predefined threshold. Our model has been evaluated on our developed platform. The extensive experimental results and analysis prove the effectiveness of our method.

关键词： Wireless communication Conferences Semantics Hidden Markov models Interference Markov processes Radiofrequency interference

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Defect Sample Generation System Based on DCGAN for Glass Package Electrical Connectors

Defect Sample Generation System Based on DCGAN for Glass Pac...

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Chinese intelligent Systems Conference, CISC 2020

作者： Liu, Qunpo Wang, Mengke Hanajima, Naohiko Department of Robotics Engineering Henan Polytechnic University 2001 Century Avenue JiaozuoHenan454003 China Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment 2001 Century Avenue JiaozuoHenan454003 China College of Information and Systems Muroran Institute of Technology 27-1 Mizumoto-cho Muroran-shiHokkaido050-8585 Japan

ISBN: (纸本)9789811584572

Precision glass packaged electrical connectors are widely used to connect precision modular electrical appliances. Manual detection is currently used due to its small size. In order to improve the detection efficiency and accuracy, deep learning is applied to the automatic detection of the defect. In this paper, in order to solve the problem of lack of defect samples, a defect sample generation system for micro-precision glass package electrical connectors based on deep convolutional generation confrontation network (DCGAN) is constructed. A network model of defect samples based on DCGAN is constructed, and algorithm design, parameter settings, network training and experiments are performed. More than 1,500 samples were generated. Finally, the generated samples were tested for defects (including missing blocks and bubbles). The results show that the samples generated by this method can be used as real samples in defect detection training. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Defects

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