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Siberian Conference on control and Communications (SIBCON)

作者： Egor S. Polyntsev Irina Y. Prokazina Aleksandr I. Bartenev Alina A. Sogomonyants Valery A. Kagadey Engeneering Center of Microwave Equipment and Technologies National research Tomsk State University Tomsk Russia Department of industrial electronics Tomsk University of Control Systems and Radioelectronics Tomsk Russia Laboratory of Robotics and Artificial Intellegence Tomsk University of Control Systems and Radioelectronics Tomsk Russia

ISBN: (纸本)9781665476294

This paper presents the results on the development, simulation and optimization of the electrical circuit diagram, as well as the layout of a monolithic GaN half-bridge integrated circuit with on-chip drivers and power e-HEMT transistors based on the GaN-on-SOI technology platform. The presented integrated circuit is an alternative to multi-chip hybrid CMOS-GaN solutions. The power stage, logic control, and high-side and low-side drivers are integrated into one chip. The simulation results demonstrate the high potential of using GaN half-bridge integrated circuits as part of high-performance electrical energy converters.

关键词： Technical requirements Portable computers Power supplies Wearable computers Simulation Layout System-on-chip

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A Real-Time Fail-Safe Algorithm for Decoding of Myoelectric Signals to control a Prosthetic Arm 21

A Real-Time Fail-Safe Algorithm for Decoding of Myoelectric ...

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21st IEEE International Carpathian control Conference, ICCC 2020

作者： Unanyan, Narek N. Belov, Alexey A. V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Laboratory of Dynamics of Control Systems Moscow Russia Faculty of Control Systems and Robotics Itmo University St. Petersburg Russia

ISBN: (数字)9781728119519

ISBN: (纸本)9781728119519

In this article a real-Time self-Tuning algorithm of detecting fingers movements based on the electromyographic (EMG) sensors is developed. A multi-level input data processing from the EMG sensor with self diagnosis is suggested. It provides the identification of muscle tension, which corresponds of several types of finger movements. This solution enables to use the lowbit controllers to manipulate the prosthetic hand. The results of system modeling and testing on the Arduino nano microcontroller demonstrated that the system identifies finger movements with high accuracy. © 2020 IEEE.

关键词： Prosthetics

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Safe operation of a modular production system via supervisor automata*

Safe operation of a modular production system via supervisor...

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Mediterranean Conference on control and Automation (MED)

作者： Fotis N. Koumboulis Dimitrios G. Fragkoulis Benise Siake Department of Digital Industry Technologies Robotics Automatic Control Cyber-Physical Systems LaboratorySchool of Science National and Kapodistrian University of Athens Euripus Campus Euboea Greece Core Department National and Kapodistrian University of Athens Euripus Campus Euboea Greece

In this paper, the three units of a Modular Production System (MPS) benchmark with a parametric number of drilling tools are modelled using finite deterministic automata in the discrete event system framework. The desired behavior of the MPS benchmark process together with the desired sequence of manufacturing actions of the MPS are expressed in the form of specification rules. The rules have been expressed in the form of a set of regular languages. Each regular language has been realized by a supervisor automaton. Using these supervisors, a modular supervisory architecture has been proposed. The physical realizability and the nonblocking property of the controlled automaton have been proved.

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Intention-Aware Planner for Robust and Safe Aerial Tracking

arXiv

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arXiv 2023年

作者： Ren, Qiuyu Yu, Huan Dai, Jiajun Zheng, Zhi Meng, Jun Xu, Li Xu, Chao Gao, Fei Cao, Yanjun The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou313000 China Huzhou Laboratory of Autonomous Intelligent Systems Huzhou313000 China The Robotics Institute Zhejiang University Yuyao315400 China College of Electrical Engineering Zhejiang University Hangzhou310027 China

Autonomous target tracking with quadrotors has wide applications in many scenarios, such as cinematographic follow-up shooting or suspect chasing. Target motion prediction is necessary when designing the tracking planner. However, the widely used constant velocity or constant rotation assumption can not fully capture the dynamics of the target. The tracker may fail when the target happens to move aggressively, such as sudden turn or deceleration. In this paper, we propose an intention-aware planner by additionally considering the intention of the target to enhance safety and robustness in aerial tracking applications. Firstly, a designated intention prediction method is proposed, which combines a user-defined potential assessment function and a state observation function. A reachable region is generated to specifically evaluate the turning intentions. Then we design an intention-driven hybrid A* method to predict the future possible positions for the target. Finally, an intention-aware optimization approach is designed to generate a spatial-temporal optimal trajectory, allowing the tracker to perceive unexpected situations from the target. Benchmark comparisons and real-world experiments are conducted to validate the performance of our method. Copyright © 2023, The Authors. All rights reserved.

关键词： Aircraft detection

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Data-based Stabilization of Unknown Discrete-time 2-D Roesser systems

Data-based Stabilization of Unknown Discrete-time 2-D Roesse...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Runmin Yang Rongni Yang Renjie Ma Yanzheng Zhu Peng Shi School of Control Science and Engineering Shandong University Jinan China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China School of Electrical and Mechanical Engineering University of Adelaide Adelaide SA Australia

ISBN: (数字)9798331528041

ISBN: (纸本)9798331528058

This paper studies the stabilization problem of discrete-time two-dimensional (2-D) systems represented by Roesser based on available data. First of all, based on the pre-collected input-state data, the original system is transformed into a data-based form. Then a set is established to represent all systems capable of generating the given data, thereby indirectly stabilizing the original system by stabilizing all systems within this set. Next, by utilizing the S-procedure, sufficient conditions are established for the resultant closed-loop systems that incorporate a state feedback controller based on collected data. Finally, an example is given to demonstrate the effectiveness of the proposed approach.

关键词： Sufficient conditions State feedback Two-dimensional displays Transforms Machine learning Stability analysis Data models Numerical models Closed loop systems Numerical stability

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Marker or Markerless? Mode-Switchable Optical Tactile Sensing for Diverse Robot Tasks

arXiv

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arXiv 2024年

作者： Ou, Ni Chen, Zhuo Luo, Shan The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China The Robot Perception Lab. Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom

Optical tactile sensors play a pivotal role in robot perception and manipulation tasks. The membrane of these sensors can be painted with markers or remain markerless, enabling them to function in either marker or markerless mode. However, this uni-modal selection means the sensor is only suitable for either manipulation or perception tasks. While markers are vital for manipulation, they can also obstruct the camera, thereby impeding perception. The dilemma of selecting between marker and markerless modes presents a significant obstacle. To address this issue, we propose a novel mode-switchable optical tactile sensing approach that facilitates transitions between the two modes. The marker-to-markerless transition is achieved through a generative model, whereas its inverse transition is realized using a sparsely supervised regressive model. Our approach allows a single-mode optical sensor to operate effectively in both marker and markerless modes without the need for additional hardware, making it well-suited for both perception and manipulation tasks. Extensive experiments validate the effectiveness of our method. For perception tasks, our approach decreases the number of categories that include misclassified samples by 2 and improves contact area segmentation IoU by 3.53%. For manipulation tasks, our method attains a high success rate of 92.59% in slip detection. Code, dataset and demo videos are available at the project website https://***/Marker-Markerless-Transition/ Copyright © 2024, The Authors. All rights reserved.

关键词： Tactile sensors

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A Haptic Exploration and Surface Classification of Objects with Four Typical Surface Properties 8

A Haptic Exploration and Surface Classification of Objects w...

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

作者： Qi, Peng Wu, Yunfeng Yao, Tianliang Lu, Bo Sun, Yi Dai, Jian S. College of Electronics and Information Engineering Tongji University Department of Control Science and Engineering Shanghai China Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Jiangsu Suzhou China Ecole Polytechnique Federale de Lausanne Laboratory of Intelligent Systems Lausanne1015 Switzerland College of Engineering Southern University of Science and Technology Department of Mechanical and Energy Engineering Shenzhen518055 China School of Natural Mathematical and Engineering Sciences King's College London United Kingdom

ISBN: (纸本)9798350300178

To effectively interact with the physical world, an intelligent robot is required to have the ability to obtain the detailed features of an unknown object. Visual devices are commonly used to detect the global geometry of an object;however, detailed information such as surface properties cannot be identified using these devices. The current study proposes an efficient haptic exploration method to recognize the physical properties of surfaces using an intelligent fingertip. Our surface-following algorithm utilizes the normal force vector and the tangential force vector at the contact point between the fingertip and the target object to predict the moving direction and implement the surface exploration. And a correction index K is introduced to adjust the sliding velocity. The algorithm is proved to be robust and high performance both in simulation and lab experiments. Finally, we propose and explore a haptic prediction neural network, which enables our robot to have an accurate feel through physical interaction. In the classification experiment of four types of objects with different surface properties, the average accuracy of the proposed model is 90.2%. © 2023 IEEE.

关键词： Surface properties

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

Temperature Rising Model of Tubular Permanent Magnet Linear ...

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Chinese control Conference (CCC)

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

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.

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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

A Weighting Factors Autotuning Strategy for Model Predictive...

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Chinese control Conference (CCC)

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

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.

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PointPillars Backbone Type Selection For Fast and Accurate LiDAR Object Detection

TechRxiv

引用

TechRxiv 2022年

作者： Lis, Konrad Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland

3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolutional neural network on detection accuracy and computation speed. We chose the PointPillars network, which is characterised by a simple architecture, high speed, and modularity that allows for easy expansion. During the experiments, we paid particular attention to the change in detection efficiency (measured by the mAP metric) and the total number of multiply-addition operations needed to process one point cloud. We tested 10 different convolutional neural network architectures that are widely used in image-based detection problems. For a backbone like MobilenetV1, we obtained an almost 4x speedup at the cost of a 1.13% decrease in mAP. On the other hand, for CSPDarknet we got an acceleration of more than 1.5x at an increase in mAP of 0.33%. We have thus demonstrated that it is possible to significantly speed up a 3D object detector in LiDAR point clouds with a small decrease in detection efficiency. This result can be used when PointPillars or similar algorithms are implemented in embedded systems, including SoC FPGAs. The code is available at https://***/vision-agh/pointpillars backbone. © 2022, CC BY.

关键词： Object detection

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