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2022 Chinese Automation Congress, CAC 2022

作者： Qian, Kang Chen, Zhihuan Sun, Yanqin Engineering Research Center for Metallurgical Automation and Measurement Technology Ministry of Education Wuhan University of Science and Technology Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781665465335

This study focuses on the synchronization problem of double-layer complex networks with time delayed coupling. Distinguish from most of previous works, a more general network model is introduced, where the number and the dimension of the nodes can be different between the drive network and the response network. This network model is more close to the practice. In order to obtain the synchronization of double-layer complex networks, an ingenious dynamic soft variable structure controller is proposed, where three sub-controllers and one adaptive observers are designed, and the stability of the controller is demonstrated by a strict mathematical proof. Numerical simulations verify the effectiveness of proposed strategy. © 2022 IEEE.

关键词： Complex networks

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STRONG: Synchronous and asynchronous RObust Network localization, under Non-Gaussian noise

arXiv

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arXiv 2021年

作者： Soares, Cláudia Gomes, João Institute for Systems and Robotics Laboratory for Robotics and Engineering Systems IST Universidade de Lisboa Portugal

Real-world network applications must cope with failing nodes, malicious attacks, or nodes facing corrupted data — data classified as outliers. Our work addresses these concerns in the scope of the sensor network localization problem where, despite the abundance of technical literature, prior research seldom considered outlier data. We propose robust, fast, and distributed network localization algorithms, resilient to high-power noise, but also precise under regular Gaussian noise. We use a Huber M-estimator, thus obtaining a robust (but nonconvex) optimization problem. We convexify and change the problem representation, to allow for distributed robust localization algorithms: a synchronous distributed method that has optimal convergence rate and an asynchronous one with proven convergence guarantees. A major highlight of our contribution lies on the fact that we pay no price for provable distributed computation neither in accuracy, nor in communication cost or convergence speed. Simulations showcase the superior performance of our algorithms, both in the presence of outliers and under regular Gaussian noise: our method exceeds the accuracy of alternative approaches, distributed and centralized, even under heavy additive and multiplicative outlier noise. Copyright © 2021, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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Rail-Guided Multi-Robot System for the Cooperative Manipulation of Cross-Scale Targets

Rail-Guided Multi-Robot System for the Cooperative Manipulat...

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IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Han Tao Huaping Wang Yaozhen Hou Siyu Guo Kaijun Lin Maolin Wang Qiang Huang Toshio Fukuda Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology China Ministry of Education Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

In the field of biomedicine, contact micromanipulations are mostly based on multi-robot coordinated operations to achieve mechanical contact interactions with a single type of target in a specific task scenario, which has advantages such as high repeatability, high precision and high stability. With the rapid development of biomedical technology, the increasingly complex biological micromanipulation process has been transformed from a single task to a task sequence of several subtasks, which puts forward higher requirements for the coordination, flexibility, operation accuracy and so on. However, due to the immutable configuration of the end-effector, most microrobotic manipulation systems have a fixed operation dimension, which makes it difficult to include the whole processing of complex tasks and meet the differentiated needs of different operational tasks and objectives. Therefore, this paper proposes a formation control based multi-robot dynamical reconfiguration collaborative micromanipulation to meet the dynamic requirements of multi-process complex tasks. By combining macro multi-robot formation control with collaborative micromanipulation, the dynamical reconfiguration of the end-effector under different manipulation tasks is realized. It can execute efficient and precise manipulation on fragile micro-objects ranging from 50 $\mu \mathrm{m}$ and 1000 $\mu \mathrm{m}$, and provide a new idea for accomplishing the whole processing of complex tasks, such as biological microassembly.

关键词： Viscosity Vibrations Rails Microscopy Collaboration End effectors Formation control

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Path Planning for Heterogeneous Robotic Delivery systems Considering Road Network Constraints

Path Planning for Heterogeneous Robotic Delivery Systems Con...

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Asian Control Conference

作者： Shangxuan Hou Zhihuan Chen Xiangkai He Xiwen Yan Zuao Wang Xiujuan Zheng Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

Heterogeneous robotic delivery system (HRDS), which is consisted of unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV), is widely used for the delivery in the lastest years. As the core of delivery industry, the path planning problem is crucial for HRDS. In HRDS model in this study, UAV can deliver multiple customer points in a single flight, thereby improving delivery efficiency. Meanwhile, the movement restrictions of UGV within the road network and the constraint of UAV endurance are considered to make the model more practical and realistic. To solve the problem, this study based on the discrete Artificial Bee Colony Algorithm (ABC), proposes encoding and decoding strategies, position updating strategies, and local search strategies to make multiple improvements to ABC. Simulation results demonstrate that modifide ABC effectively resolves this problem, exhibiting faster convergence speed and higher solution accuracy compared to other algorithms.

关键词： Accuracy Service robots Roads Simulation Urban areas Autonomous aerial vehicles Search problems

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Emotion Classification based on Multi Physiological Signals Using Hybrid Fusion Strategy

Emotion Classification based on Multi Physiological Signals ...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Jiacheng Wan Yinfeng Fang Chunsheng Guo Zhaojie Ju Dalin Zhou Pinghu Digital Technology Innovation Research Institute School of Communication Engineering Hangzhou Dianzi University Hangzhou China Intelligent Systems and Biomedical Robotics Group School of Computing University of Portsmouth Portsmouth UK

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

The demand for emotion recognition is increasing not only in daily life but also in professional domains such as disease diagnosis and clinical rehabilitation. By monitoring non-invasive physiological signals of patients, providing timely feedback on their emotional state can significantly aid in patient recovery and subsequent expert treatment evaluation. In this study, we propose a mutual fusion approach utilizing both feature fusion and decision fusion techniques for emotion classification. Firstly, statistical knowledge-based methods were employed to select physiological signals and extract highly correlated and complementary features for feature-level fusion. Subsequently, a similarity weight, based on feature selection and statistical analysis, was incorporated into the decision fusion process. Our proposed method yielded promising results, achieving 82.5% accuracy and 75.2% macro f1 score for three-class classification (neutral vs. stress vs. amusement), 95.4% accuracy and 94.6% macro f1 score for two-class classification (stress vs. non-stress) using publicly available data from the WESAD dataset. These results demonstrate that employing a mutual fusion approach outperforms single fusion methods in emotion classification tasks.

关键词： Accuracy Mechatronics Statistical analysis Machine vision Anxiety disorders Knowledge based systems Feature extraction Medical diagnosis Biomedical monitoring Monitoring

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Online Multi-Contact Feedback Model Predictive Control for Interactive Robotic Tasks

Online Multi-Contact Feedback Model Predictive Control for I...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Seo Wook Han Maged Iskandar Jinoh Lee Min Jun Kim Intelligent Robotic Systems Laboratory Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Institute of Robotics and Mechatronics German Aerospace Center (DLR) Wessling Germany Department of Mechanical Engineering KAIST Daejeon Republic of Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this paper, we propose a model predictive control (MPC) that accomplishes interactive robotic tasks, in which multiple contacts may occur at unknown locations. To address such scenarios, we made an explicit contact feedback loop in the MPC framework. An algorithm called Multi-Contact Particle Filter with Exploration Particle (MCP-EP) is employed to establish real-time feedback of multi-contact information. Then the interaction locations and forces are accommodated in the MPC framework via a spring contact model. Moreover, we achieved real-time control for a 7 degrees of freedom robot without any simplifying assumptions by employing a Differential-Dynamic-Programming algorithm. We achieved 6.8kHz, 1.9kHz, and 1.8kHz update rates of the MPC for 0, 1, and 2 contacts, respectively. This allows the robot to handle unexpected contacts in real time. Real-world experiments show the effectiveness of the proposed method in various scenarios.

关键词： Feedback loop Prediction algorithms Real-time systems Particle filters Task analysis Springs Robots

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Trajectory Tracking of Fractional order Quadrotor UAV Based on Adaptive Fuzzy Fractional Order PID Controller

Trajectory Tracking of Fractional order Quadrotor UAV Based ...

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Asian Control Conference

作者： Shiyu Xi Zhihuan Chen Zhiheng Chen Yang Chen Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In this paper, the trajectory tracking problem of the quadrotor UAV with fractional order characteristics is studied. First, an accurate fractional order mathematical model is innovatively established, addressing the deficiency of traditional integer order models in modeling precision. Secondly, the prediction-correction algorithm is applied to solve these complex fractional order differential equations. In design of the control system, the adaptive fuzzy fractional order PID (AFFOPID) control strategy is applied to the position subsystem and attitude subsystem of the quadrotor UAV, dealing effectively with the fractional order characteristics and also enhancing control flexibility. Since the AFFOPID controller does not require the integral term of the error as input, it can be more easily applied and tuned in practical situations. Finally, comparative simulation experiments are conducted to confirm the effectiveness of the proposed control strategy and the superiority of fractional order controllers.

关键词： Adaptation models Trajectory tracking Differential operators Autonomous aerial vehicles Control systems Prediction algorithms Mathematical models

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Tacking Control of Multi-UAV formation under interference

Tacking Control of Multi-UAV formation under interference

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Asian Control Conference

作者： Zhiheng Chen Zhihuan Chen Changjun Li Huaiyu Wu Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In this paper, the matching of position tracking and flight speed in multi-UAV formation control is studied, and the hierarchical control strategy based on the virtual structure method is constructed. Firstly, a second-order dynamic model with disturbances is introduced to address the inadequacy of the traditional first-order dynamics model lack of consideration for the coupling of position and attitude loops. Secondly, a high-level formation controller based on the sliding mode theory is designed. Further, based on the output information of the high-level, a fractional order terminal sliding mode low-level controller is proposed to ensure the robustness of the formation tracking process. In addition, a neural network-based sliding mode observer is designed to approximate the uncertainty of the system to improve the immunity to interference. Finally, simulation experiments verify the effectiveness of the proposed strategy,

关键词： Uncertainty Systematics Trajectory tracking Interference Autonomous aerial vehicles Formation control Stability analysis

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Efficient Learning and Control of String- Type Artificial Muscle Driven Robotic systems

Efficient Learning and Control of String- Type Artificial Mu...

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American Control Conference (ACC)

作者： Jiyue Tao Sunil Kumar Rajendran Yunsong Zhang Feitian Zhang Dexin Zhao Tongsheng Shen The Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China The National Innovation Institute of Defense Technology Beijing China The BSS Technologies Inc. Takoma Park MD USA The Department of Advanced Manufacturing and Robotics The State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing China

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper investigates the learning-based control of robotic systems driven by string-type artificial muscles. Due to the highly nonlinear dynamics of the actuators and the complicated mechanical structure, it is typically very challenging to design traditional model-based controllers that exhibit desired control performances. With the rapid development of machine learning techniques, deep reinforcement learning (DRL) algorithms have been utilized to control a variety of complex robotic systems. However, these DRL algorithms usually require a huge amount of training data and iterations to converge, which is generally unacceptable for the robotic systems of interest. Therefore, this paper designs an efficient learning-based control algorithm, aiming to improve the training efficiency for robotic systems driven by string-type artificial muscle actuators. Specially, two training improvements are proposed including imitation learning and data augmentation. This paper applies the proposed learning methods to three popular DRL algorithms and tests the control performances in three case studies using three string-type artificial muscle-driven robots, including a parallel robotic wrist, a two degrees-of-freedom (DOF) robotic eye and a robotic finger. Simulation results show that the proposed learning-based control methods significantly accelerate the convergence speed and improve the data efficiency in all the three case studies.

关键词： Artificial muscles Wrist Training Actuators Machine learning algorithms Imitation learning Fingers

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Biodegradable Gliding Paper Flyers Fabricated Through Inkjet Printing

Biodegradable Gliding Paper Flyers Fabricated Through Inkjet...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Luca Girardi Rui Wu Yuki Fukatsu Hiroki Shigemune Stefano Mintchev Department of Environmental Systems Science Environmental Robotics Laboratory ETH Zurich Zurich Switzerland Swiss Federal Institute for Forest Snow and Landscape Research (WSL) Birmensdorf Switzerland Department of Electrical Engineering Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Seed-inspired minimalist microflyers are showing potential as dispersal platforms for sensor networks and seeds. Their function relies on the sheer number of low-cost flyers, inevitably raising concerns about the post-operation environmental impact. We propose a biodegradable paper glider platform fabricated through origami inkjet printing. This method can fold origami along printing patterns on different paper varieties. We created a printing pattern that allows 2D paper sheets to self-fold into a 3D flying wing glider with designable wing geometry and center of gravity (CG). The design allows stable and repeatable gliding behavior, proven in our gliding tests. It successfully achieves the dispersal of multiple gliders from a hovering drone, covering an average horizontal distance larger than the release height. We also tested the biodegradation of different paper types compatible with the printing method, showing near-complete degradation after 15 weeks in moist soil. Our study presents a novel, potentially scalable approach for fabricating environmentally friendly microflyers, offering new avenues for remote environmental sensing and automated forest restoration programs.

关键词： Geometry Atmospheric modeling Forestry Aerodynamics Three-dimensional printing Stability analysis Ink jet printing Seeds (agriculture) Thermal stability Paints

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