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2023 International Conference on Biomimetic Intelligence and robotics

作者： Liu, Yuexun Liu, Du-Xin Ma, Yue Guo, Sheng Wu, Xinyu Robotics Research Center School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

With the expansion of application scenarios, the walking-assisted lower-limb exoskeleton robot urgently needs to improve its walking ability in complex terrains. However, due to the lack of environmental understanding ability and decision-making ability, the exoskeleton can not meet the need of people with lower-limb disability in complex terrains. To improve the walking abillity, this paper proposes a method of predicting the landing area in complex terrains for walking-assisted lower-limb exoskeleton robot. Multiple sensors were used to obtain the terrain information, step length, and stride length of human walking, and a multi-type input convolutional network was built to establish the mapping relationship to learn the decision-making mechanism of human standing in a complex environment. The result shows that the established network effectively predicts the landing area. Under the condition of full training, the predicted position deviation of the landing area is controlled within 6%, and the prediction rationality of the landing area can reach 90%. © 2023 The Authors. Published by Elsevier B.V.

关键词： Decision making

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DEGAS - Deformation Estimation based on Magnetic Gradient Tensor Contraction for Soft Robot Shape Servoing

DEGAS - Deformation Estimation based on Magnetic Gradient Te...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Jelena Vuletić Bruno Marić Matko Orsag LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9798331520205

ISBN: (纸本)9798331520212

This work proposes the first derivation, implementation, and experimental validation of magnetic-based proprioceptive sensing method for soft robotic applications. In our proposed approach, the magnetic sensing system measures gradient tensor contractions that can be directly related to the shape of a deformable plastering tool. Custom-designed and 3D-printed plastering tool embeds two identical permanent magnets that generate a non-symmetric magnetic field tracked by the proposed sensor. Seamless real-time control is enabled with the sensor sampling rate of 1 kHz. Classical linear control is synthesized for the scraper bending angle and orientation control. The tool, sensor, and the proposed control system are validated on robotic plastering and painting tasks.

关键词： Magnetic field measurement Tensors Deformation Shape Propioception Estimation Bending Soft robotics Sensors Painting

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Graph-Based Decentralized Exploration and Semantic Inspection for Multi-Robot Systems

Graph-Based Decentralized Exploration and Semantic Inspectio...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Nada E. Abbas Tamara Petrovic Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Zagreb Croatia

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This paper presents a decentralized graph-based exploration and inspection framework for Multi-Robot Systems, designed to address challenges in subterranean and largescale environments. Unlike prior works that focus solely on exploration or inspection, this framework integrates volumetric exploration, semantic inspection, and dynamic task allocation into a unified decentralized system. A key novelty of this work is the seamless integration of these modules in a multi-robot setting, allowing UAVs to autonomously coordinate their tasks without relying on centralized control. The framework employs a hierarchical graph structure, utilizing a dense local graph for immediate navigation and a sparse global graph for long-term planning and repositioning. Extensive simulations in large-scale complex-shaped environments demonstrate that the proposed approach improves the completeness of the generated maps, reduces inconsistencies in the constructed mesh, and accelerates the overall exploration-inspection process compared to existing decentralized strategies.

关键词： Semantics Inspection Prediction algorithms Dynamic scheduling Aircraft navigation Robustness Planning Multi-robot systems Resource management Centralized control

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Flexible job shop machines and AGVs cooperative scheduling on the basis of DQN algorithm 6

Flexible job shop machines and AGVs cooperative scheduling o...

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6th IEEE Advanced Information Management, Communicates, Electronic and Automation control Conference, IMCEC 2024

作者： Xiaoting, Dong Guangxi, Wan Peng, Zeng Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

ISBN: (纸本)9798350316520

In flexible job shop, the transportation time and path of Automated Guided Vehicles (AGVs) greatly impact the production cycle time. However, traditional flexible job shop scheduling problems (FJSSP) mainly focus on job sequencing and machine selection, neglecting the effect of AGVs transportation on the production process. This often leads to suboptimal scheduling solutions that are difficult to guide the shop floor operation effectively. To address this issue, this paper formulates a cooperative scheduling model that integrates the AGVs scheduling into traditional flexible job shop scheduling problem, abbreviated as the FJSMAS problem, with the objective of makespan minimization. Furthermore, by designing state features, action space, and reward function, the FJSMAS problem is transformed into a Markov decision process, a deep reinforcement learning algorithm (DRL) is then adopted to solve it. The feasibility of the proposed FJSMAS model and the effectiveness of DRL algorithm in solving the FJSMAS problem are verified through benchmark's instances. © 2024 IEEE.

关键词： Reinforcement learning

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A Weighting Factors Autotuning Strategy for Model Predictive Torque control of Permanent Magnet Synchronous Motor Based on Adaptive Multi-Objective Black Hole Algorithm 42

A Weighting Factors Autotuning Strategy for Model Predictive...

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42nd Chinese control Conference, CCC 2023

作者： Zhou, Zixiang Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

The rational design of weighting factors in the cost function for finite control set model predictive torque control (FCS-MPTC) has been a matter of great interest in power electronics and electrical drives. In order to solve this problem, a weighting factors autotuning strategy for FCS-MPTC of permanent magnet synchronous motor (PMSM) based on the adaptive multi-objective black hole algorithm (AMOBH) is proposed. In this paper, the design process of the FCS-MPTC algorithm is first analyzed in detail. Then, an AMOBH algorithm that can take into account both population convergence and population diversity is introduced, and based on this algorithm, the design problem of the weighting factors is successfully transformed into a multi-objective optimization problem by means of reconstructing the cost function and designing the motor operation information collected in real time as the objective functions of the multi-objective optimization algorithm. Simulation results show that the proposed method can find a set of weighting factor combinations suitable for different working condition requirements, and these weighting factors can effectively improve the operation performance of the PMSM system. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Cost functions

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Local Path Planning Combined with the Motion State of Dynamic Obstacles 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Hu, Yuxin Li, Jun Jiang, Lin Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science and Technology Wuhan430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Aiming at the problem that the current local path planning algorithm treats moving obstacles as transient static ones when avoiding obstacles, lacking initiative and security, a local path planning algorithm combining dynamic obstacle motion state is proposed. Firstly, the position information of all obstacles is obtained by a single scan LIDAR. Then, segmenting and linearly fitting all laser point clouds, removing the known obstacles in the map;and marking possible emerging dynamic obstacles with circles of appropriate size;then detecting the dynamic obstacles through the change of the coordinates of the center of the circle, obtaining the center coordinates of the dynamic obstacles continuously;thus, the equation of motion is solved by using the least squares. Finally, the cost map of dynamic obstacles is expanded in the direction of velocity, by combining DWA dynamic window method to realize avoiding dynamic obstacles safely. In this paper, through the simulation experiments and real environment experiments of robot meeting scenes from multiple angles, the results show that expanding the cost map of the motion direction of the dynamic obstacles provides more sufficient response space for the robot to avoid the dynamic obstacles. Compared with the original DWA, the algorithm in this paper can avoid dynamic obstacles more safely, which proves the security and feasibility of this algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Equations of motion

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Temperature Rising Model of Tubular Permanent Magnet Linear Synchronous Motor Based on Transfer Learning-Deep Neural Network 42

Temperature Rising Model of Tubular Permanent Magnet Linear ...

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42nd Chinese control Conference, CCC 2023

作者： Wang, YiFei Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

High temperature rise of permanent magnet linear synchronous motor can lead to irreversible demagnetization of the motor permanent magnet, which can negatively affect the motor performance. To address this problem, a thermal modeling analysis method based on Transfer learning-Deep neural network (TL-DNN) was proposed in this paper. Its specific implementation steps include (1) corresponding to different heat source inputs, the equivalent thermal circuit method and the finite element analysis was adopted based on the structure and main parameters of PMLSM including overall average temperature rise, coil temperature rise and permanent magnet temperature rise from the data sets of the motor;(2) TL-DNN was used to fit the functional relationship between the input source features and the output targets based on the characteristics of the sample data sets. In order to verify the accuracy of the prediction model with small sample data sets, this paper divided the proportion of the data set and compared the results with other classic nonparametric models (random forest, support vector machine, and deep neural network). The results show that the TL-DNN model outperforms other machine learning models and has better robustness and generalization ability when the training datasets are insufficient, and achieves an organic combination of physical field path model and data-driven model, which provides a feasible solution for PMLSM modeling in the case of small samples. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Finite element method

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A new active rehabilitation training mode for upper limbs based on Tai Chi Pushing Hands

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Biomimetic Intelligence & robotics 2024年第3期4卷 82-92页

作者： Xiangpan Li Liaoyuan Li Jianhai Han Bingjing Guo Ganqin Du School of Mechatronics Engineering Henan University of Science and TechnologyLuoyang 471003China Henan Provincial Key Laboratory of Robotics and Intelligent Systems Luoyang 471003China School of Automotive Engineering Hubei University of Automotive TechnologyShiyan 442002China Hubei Key Laboratory of Automotive Power Train and Electronic Control Shiyan 442002China The First Affiliated Hospital of Henan University of Science and Technology Luoyang 471003China

Robot-assisted rehabilitation is a crucial approach to restoring motor function in the ***,the current training trajectory lacks sufficient theoretical or practical support,and the monotony of single-mode training is a *** Chi Pushing Hands,a beneficial and effective daily exercise,has been shown to improve balance function,psychological state,and motor function of the upper extremities in patients recovering from *** address these issues,we propose a new active rehabilitation training that incorporates Tai Chi Pushing Hands movements and yin-yang balance *** training trajectory and direction are encoded by the velocity field and consist of two processes:yang(push)and yin(return).During yang,the limb actively pushes the robot to move,while during yin,the limb actively follows the robot’s *** provide necessary assistance,an admittance controller with self-adaptive parameters is *** addition,we introduce two indexes,the‘Intention Angle’(ϖ)and the time ratio(Γ),to evaluate motion perception *** experiment was conducted on a 4-degree-of-freedom upper limb rehabilitation robot platform,and the subjects were separated into a familiar group and an unfamiliar *** experiment results show that the training could be completed well no matter whether the subject is familiar with Tai Chi Pushing Hands or *** parameters and the movement of the robot can be adjusted based on the interactive force to adapt to the ability of the subject.

关键词： Tai Chi Push Hands Velocity field Self-adaptive admittance Upper limb rehabilitation Active training

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A new SPICE modeling approach of annular MOSFET in 350 nm commercial CMOS process 3

A new SPICE modeling approach of annular MOSFET in 350 nm co...

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3rd International Conference on Electronic Information Engineering and Computer, EIECT 2023

作者： Cheng, He Yang, Zhijia Zhang, Chao Zhang, Zhipeng Key Laboratory of Networked Control Systems Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350357707

Annular gate MOSFETs have emerged as potential solutions for radiation-hardened electronics, demonstrating exceptional total ionizing dose tolerance. However, accurate modeling of annular MOSFETs is crucial when designing analog integrated circuits for use in radiation environments, especially when implementing commercial CMOS processes. To enable circuit simulation using tools like SPECTRE/SPICE, foundry-provided PDKs must incorporate a rigorously verified compact model of annular MOSFET behavior. TCAD simulation can then be used to numerically evaluate the current characteristics of the annular MOSFET against the refined compact model constructed from the foundry-provided PDK. In this paper, by aligning the current characteristics of a standard NMOS between TCAD and SPICE simulations, we can verify the material process conditions. Then, based on the material process parameters, the model of the annular gate MOSFET is established using the TCAD simulator. Finally, reasonable agreements are obtained between the TCAD and SPICE simulation results for the IDS-VGS and IDS-VDS characteristics. © 2023 IEEE.

关键词： Foundries

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Power Line Following Based on Measurements of the Magnetic Field

Power Line Following Based on Measurements of the Magnetic F...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Goran Vasiljević Dean Martinović Stjepan Bogdan Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Unska 3 University of Zagreb Zagreb Croatia

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

In this paper, we present a method to control the UAV to follow the power line with a specific position and orientation based only on the measurement of the magnetic field generated by the current flow in the power line. In this way, it is possible to localize the UAV with respect to the power line without the need for additional sensors, even in poor visibility conditions. The measurements from four magnetometers attached to the UAV are used to solve an optimization problem that involves determining the relative pose of the UAV with respect to the power line. Based on the relative pose, the UAV is controlled to follow the power line in a predefined position and orientation. Experiments in a test setup have confirmed that the method is applicable in a realistic environment.

关键词： Location awareness Visualization Power measurement Magnetic field measurement Magnetometers Current measurement Position measurement Autonomous aerial vehicles Magnetic fields Optimization

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