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Learning-based robot assembly method for peg insertion tasks on inclined hole using time-series force information

Biomimetic Intelligence & robotics 2025年第1期5卷 116-123页

作者： Zhifei Shen Zhiyong Jiang Jingwang Zhang Jun Wu Qiuguo Zhu Polytechnic Institute Zhejiang UniversityHangzhou 310015China Robotics Engineering Center the 21st Research Institute of China Electronics Technology Group CorporationShanghai 200233China Department of Control Science and Engineering Zhejiang UniversityHangzhou 310027China

This paper presents a novel method for learning force-aware robot assembly skills,specifically targeting the peg insertion task on inclined *** the peg insertion task involving inclined holes,we employ one-dimensional convolutional networks(1DCNN)and gated recurrent units(GRU)to extract features from the time-series force information during the assembly process,thereby identifying different contact states between the peg and the *** to the identification of contact states,corresponding pose adjustments are executed,and overall smooth interaction is ensured through admittance *** assembly process is dynamically adjusted using a state machine to fine-tune admittance control parameters and seamlessly switch the assembly *** the utilization of dual-arm clamping,we conduct key unlocking experiments on bases inclined at varying *** results demonstrate that the proposed method significantly improves the accuracy and success rate of state recognition compared to previous methods.

关键词： Manipulator assembly Peg insertion Force information Contact state Dual-arm

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Long-Range Vehicle Detection of LiDAR using Adaboost Classification

Long-Range Vehicle Detection of LiDAR using Adaboost Classif...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Lim, Na-Young Lee, Jeon-Hyeok Park, Tae-Hyoung Chungbuk National University Department of Intelligent Systems & Robotics Cheongju Korea Republic of Chungbuk National University Department of Control & Robot Engineering Cheongju Korea Republic of

ISBN: (纸本)9798331531614

In recent developments, autonomous racing has garnered attention as it aims to overcome the limitations of standard autonomous driving systems. Achieving safe racing conditions necessitates both fast and long-range perception. However, current 3D LiDAR object detection methods face challenges with high computational costs and limited detection ranges. These issues make them unsuitable for racing scenarios. To address these challenges, this paper proposes a clustering-based long-range vehicle detection method that relies solely on LiDAR. First, the method removes ground points and foreground points and clusters the remaining points. Subsequently, these clusters are classified as vehicles using AdaBoost, generating 2D bounding boxes in the range view. Experimental results demonstrate superior performance, achieving a computational efficiency of 53 Hz and a long-range detection accuracy of over 80%, compared to voxel-based and range-based methods. This approach offers a viable solution for autonomous racing environments. © 2025 IEEE.

关键词： Autonomous vehicles

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Model Predictive control for Systems with Limited State Variables

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Russian Electrical engineering 2023年第2期94卷 77-83页

作者： Bogdanov, A.N. Anuchin, A.S. Demidova, G.L. Department of Electric Drive Moscow Power Engineering Institute Moscow111250 Russia Faculty of Control System and Robotics ITMO University St. Petersburg197101 Russia

Abstract: Model predictive control are actively used in industry in high-power electric drives, in which it is permissible to use expensive programmable logic matrices that provide calculations with a prediction horizon of up to ten epochs and a forecast tree of several million variants. However, the computing power of microcontrollers is not enough to implement such systems in a low-power electric drive. The development of microcontrollers is following the path of increasing not only computing power, but also memory, which makes it possible to implement model predictive control systems in practice using lookup table methods for calculating control actions for all combinations of state variables and control actions. The paper shows the possibility of designing control with prediction for two types of electric drives—a DC electric drive and a switched reluctance electric drive—as objects with a small number of state variables, which allows one to fit the precalculated lookup tables of control actions in the memory of the microcontroller. Studies on mathematical models have shown that model predictive control with a finite control set and a single prediction horizon has disadvantages due to variable switching frequency, and control with a continuous control set implemented by the lookup table method allows one to perform control calculations immediately before the start of the next pulse width modulation period, reducing the algorithm execution time by hundreds of times. © 2023, Allerton Press, Inc.

关键词： Forecasting

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Research study of image classification algorithms based on Convolutional Neural Networks 24

Research study of image classification algorithms based on C...

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24th International Carpathian control Conference, ICCC 2023

作者： Nawrocka, Agata Nawrocki, Marcin Kot, Andrzej AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Department of Process Control Krakow Poland

ISBN: (纸本)9798350310221

The beginning of the paper introduces the idea of neural networks by presenting the neuron models and artificial neural networks. Next, the flow of operations used in the development of convolutional neural networks is presented, as well as an overview of popular architectures used in model development. After introducing the theoretical issues, a project using the EfficientNet architecture to recognize medical images taken by MRI is presented. The project describes: the selection and parameters of the MRI image database representing different types of brain tumors, the process of implementation and appropriate modification of the EfficientNet architecture used to classify images, the presentation of the results of learning the convolutional neural network and the images that highlight on the basis of which area the convolutional neural network classifies images. © 2023 IEEE.

关键词： Convolutional neural networks

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Identify the objective parameters of direct communication between PLC and MS SQL server 24

Identify the objective parameters of direct communication be...

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24th International Carpathian control Conference, ICCC 2023

作者： Flaga, Stanislaw Majcher, Maciej AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Department of Process Control Krakow Poland

ISBN: (纸本)9798350310221

When building digital twins of existing technical solutions, we need a large amount of data on the parameters of their operation under various conditions. The source of data on the values of process variables at the lowest level is control devices - most often PLCs. There are many ways to acquire the qualities of process variables available from the PLC level. Increasingly, OPC UA is replacing the OPC model, and the OPC UA server is increasingly a functionality of the PLC CPU. The Industrial Internet of Things IIoT is used in companies moving toward Factory 4.0. Data from controllers can be acquired using high-level languages such as C++, C# or Python. Libraries often made available under an open-source license are used for this. For example, you can find commercial libraries for communication between PLCs of selected manufacturers and MySQL servers. Siemens provides a library for communication between S7-1200/1500 controllers and MS SQL server. The author has yet to find an exhaustive analysis of such a solution. In the literature, there need to be more studies of experiments describing the performance of query generation and execution and the impact of the library on PLC performance. The article presents the results of an experimental study of this issue. © 2023 IEEE.

关键词： Libraries

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A control Theoretic Study on Omnidirectional MAVs with Minimum Number of Actuators and No Internal Forces at Any Orientation 63

A Control Theoretic Study on Omnidirectional MAVs with Minim...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Ali, Ahmed Gabellieri, Chiara Franchi, Antonio Faculty Robotics and Mechatronics Department Enschede7500 AE Netherlands Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy

ISBN: (纸本)9798350316339

We propose a new multirotor aerial vehicle class of designs composed of a multi-body structure in which a main body is connected by passive joints to links equipped with propellers. We have investigated some instances of such class, some of which are shown to achieve omnidirectionality while having a minimum number of inputs equal to the main body Degrees of Freedom DoF's, only uni-directional positive thrust propellers, and no internal forces generated at steady state. After dynamics are derived following the Euler-Lagrange approach, an I/O dynamic feedback linearization strategy is then used to show the controllability of any desired pose with stable zero dynamics. We finally verify the developed controller with closed-loop simulations. © 2024 IEEE.

关键词： Feedback linearization

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Automated Classification of VMT Pathology from Optical Coherence Tomography B-scans 25

Automated Classification of VMT Pathology from Optical Coher...

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25th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2022

作者： Marciniak, Tomasz Stankiewicz, Agnieszka Institue of Automatic Control and Robotics Robotics and Electrical Engineering Poznan University of Technology Department of Automatic Control Poznan Poland

ISBN: (数字)9788362065424

ISBN: (纸本)9788362065424

The research presented in this article aims to determine the possibility of identifying macular pathologies from optical coherence tomography (OCT) images. Early detection of a pathology in the human eye retina is beneficial for patient recovery. Disorders commonly evaluated in clinical practice and research are drusen in age-related macular degeneration (AMD), diabetic macular edema (DME), and choroidal neovascularization (CNV). Our work extends this set of pathologies to include the pathology associated with improper posterior vitreous detachment, namely vitreomacular traction (VMT). Experimental research was based on single line OCT B-scans of healthy eyes and eyes with the investigated pathologies. AMD, DME and CNV images were taken from a public OCT dataset for retina classification, while healthy subjects and VMT images were acquired using an Avanti Optovue device. The accuracy results of more than 97% show the possibility of automatic preliminary diagnosis and differentiation between macular pathologies. © 2022 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Optical tomography

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Navigating the Future: Advancing Autonomous Vehicles through Robust Target Recognition and Real-Time Avoidance 4

Navigating the Future: Advancing Autonomous Vehicles through...

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4th International Conference on control Theory and Applications, ICoCTA 2024

作者： Hussein, Mohammed A. M. Habib, Maki K. The American University in Cairo Robotics Control and Smart Systems Cairo Egypt The American University in Cairo Department of Mechanical Engineering Cairo Egypt

ISBN: (纸本)9798331506155

This research addresses the critical challenge of enhancing object recognition and real-Time response capabilities in autonomous vehicles (AVs) under varying simulated conditions, which is crucial for ensuring both navigational safety and operational efficiency. Utilizing the Carla 0.9.14 simulator and Unreal Engine 4.26 on Ubuntu 20.04, we focus on improving the detection and classification of key on-road obstacles-vehicles, pedestrians, and cyclists-using the YOLOv7 object detection algorithm. By integrating advanced sensory technologies, specifically stereo vision cameras and LIDAR, we create a dynamic testing environment that simulates diverse urban and rural scenarios. Our methodology enhances the YOLOv7 algorithm's accuracy and speed through extensive training on a meticulously curated dataset of 4,113 images, reflecting a broad spectrum of environmental conditions, including varying lighting and weather conditions. This rigorous approach yielded a significant increase in mean average precision (mAP) from 64.3% to 76.3%, and enhanced the algorithm's reliability, with notable improvements over previous models. The research delineates a clear advancement in AV technology by demonstrating substantial improvements in object detection metrics, contributing foundational insights for future implementations in real-world settings and supporting the further development of real-Time avoidance systems. This study not only progresses the field of AV but also sets a new benchmark for object detection performance, aligning with industry and academic goals to optimize AV systems for complex and unpredictable driving scenarios. © 2024 IEEE.

关键词： Stereo image processing

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Exploration of Unknown Environment using Deep Reinforcement Learning

Exploration of Unknown Environment using Deep Reinforcement ...

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2023 International Conference on robotics and Automation in Industry, ICRAI 2023

作者： Ali, Asad Gul, Sarah Mahmood, Tallat Ullah, Anayat Control Automotive and Robotics Lab Rawalpindi Pakistan Balochistan University of IT Engineering and Management Sciences Department of Electrical Engineering Quetta Pakistan

ISBN: (纸本)9781665464727

Exploring the unknown environment is a very crucial task where human life is at risks like search and rescue operations, abandoned nuclear plants, covert operations and more. Autonomous robots could serve this task efficiently. The existing methods use uncertainty models for localization and map building to explore the unknown areas requiring high onboard computation and time. We propose to use Deep Reinforcement Learning (DRL) for the autonomous exploration of unknown environments. In DRL, the agent interacts with the environment and learns based on experiences (feedback/reward). We propose extrinsic and curiosity-driven reward functions to explore the environment. The curiosity-based reward function motivates the agent to explore unseen areas by predicting future states, while the extrinsic reward function avoids collisions. We train the differential drive robot in one environment and evaluate its performance in another unknown environment. We observe curiosity-driven reward function outperformed the extrinsic reward by exploring more areas in the unknown environment. The test results show the generalization capability to explore unknown environments with the proposed methods. © 2023 IEEE.

关键词： Mobile robots

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Gait dynamic stability evaluation on inclined surfaces for inverted or everted feet walking

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Fuss und Sprunggelenk 2024年第4期22卷 254-268页

作者： Raza, Anam Mahmood, Imran Sultana, Tayyaba Sultana, Salma Dehghani-Sanij, Abbas A. Department of Zoology Government College University Faisalabad Pakistan Mechatronics and Control Engineering Department Faisalabad Campus UET Lahore Pakistan Institute of Design Robotics and Optimisation School of Mechanical Engineering University of Leeds United Kingdom

Background: This study investigates gait dynamic stability on inclined surfaces while walking with foot rotational impairments such as everted and inverted feet. Walking stability is assessed during gait transitional periods i.e. weight loading and unloading phases. Methods: Foot rotational impairments (eversion and inversion) are imitated using wedged foot insoles. A total of ten healthy subjects performed five trials for each of the inverted, everted, and normal feet conditions. Experimental data was collected using a twelve-camera motion capture system and a force plate installed on an inclined platform. Lower limb joint kinematics were computed in Visual-3D motion analysis software to evaluate the degree of foot rotational impairments. Gait dynamic stability was assessed by analysing the centre of mass and centre of pressure signals as neuromechanical input and output responses respectively. Both signals were modelled in time and frequency domains and stability margins were quantified by applying Nyquist and Bode (N&B) methods from control engineering theory. Results: Stability margins quantified from N&B methods illustrated the loading phase as stable and the unloading phase as unstable gait transitions. During the loading phase, both rotational impairments illustrated a decrease in stability (p < 0,05) for the ramp ascent walk and an increase in stability (p < 0,05) for the ramp descent walk. However, there was no difference observed for the respective unloading phases. Results from neuromotor outputs (CoP-velocity) illustrated a strong interlimb correlation (p < 0,001) during gait transitional periods, implying a compensatory stability interaction exists between opposite limbs. Further, stabilities quantified from outputs were found greater in magnitudes than the instability quantified from inputs illustrating the robustness of neuromotor balance control. Conclusions: Results support the hypothesis that gait stability gets affected while walking with rotation

关键词： Balance control Foot Gait stability Inclined walk Rotational impairments

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