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Continuous Path Tracking of Robots Based on Positioning Error Compensation With Iterative Learning Control

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Liu, Ying Li, Yuwen Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai201900 China East China Jiaotong University School of Mechatronics and Vehicle Engineering Nanchang330013 China

Due to the inaccuracy of absolute positioning, it is still challenging to apply industrial robots for precise and efficient tracking of the end-effector tool along a continuous path, especially for those frequently changing robotic operations within low-volume and high-mix scenarios. To overcome this problem, this work proposes a method of continuous path tracking of robots with iterative learning control (ILC) such that the pose errors of the tool along the path can be compensated by the robot. An optical tracking system is integrated to measure the tool pose. Developed from a comprehensive kinematic error model that incorporates errors in the Denavit-Hartenberg (D-H) parameters and errors induced by the installation of the robot base and the tool, the ILC algorithm can convert the tool pose error into the joint angle compensation for the robot. The robustness of the algorithm is analyzed to prove that the compensated path approaches the desired path as the number of iterations increases. An experimental test of continuous path tracking has been performed with a UR10 robot to validate the proposed method. It is demonstrated that the average and maximum position errors can be reduced from 14.57 and 20.31 to about 0.26 and 0.78 mm, respectively. The average and maximum orientation errors are reduced from 0.66° and 0.94° to about 0.08° and 0.20°, respectively. For a test of robotic laser cutting, the average dimensional accuracy of the rectangular workpiece can be reduced from 0.416 to about 0.154 mm, and the average shape accuracy is reduced from 0.101° to about 0.059°. Using the ILC algorithm and the measurement with the optical tracking system, our method can significantly enhance the tracking accuracy of the end-effector tool along continuous paths by autonomous adjustment of the joint angles without the need for human teaching. © 2025 IEEE.

关键词： Industrial robots

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Eye movement features in solving Sternberg Memory Task 6

Eye movement features in solving Sternberg Memory Task

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6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022

作者： Brusinskii, Nikita Badarin, Artem Hramov, Alexander Immanuil Kant Baltic Federal University Baltic Center for Neurotechnologies and Artificial Intelligence Kaliningrad Russia Innopolis University Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis Russia

ISBN: (数字)9781665461740

ISBN: (纸本)9781665461740

Oculomotor activity is an important component of human mental processes, and decoding this activity can be applied in many applied fields. This paper analyzed the physiological and behavioral characteristics of a person during a prolonged solution of a cognitive task based on the Sternberg paradigm. A number of trends in changes in both physiological and behavioral characteristics over the course of the experiment were revealed. For example, an increase in subjective fatigue over the course of the experiment. In addition, correlation analysis were performed. In particular, a correlation was found between subjective fatigue and the amplitude of pupil dilation during letter set demonstrations. © 2022 IEEE.

关键词： Eye movements

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A Trajectory Planning Algorithm of Spray Robot for Workpieces with Complex Geometric Features based on 3D Point Cloud 5

A Trajectory Planning Algorithm of Spray Robot for Workpiece...

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5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Kong, Minxiu Li, Ang Gao, Feng Harbin Institute of Technology School of Mechatronics Engineering Harbin China State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9781665415989

Trajectory planning of spray robot for workpieces with complex geometric features is always a challenging problem. Combined with the actual process requirements of surface spraying and edge spraying, a new spraying path design method based on 3D point cloud is proposed in this paper. During surface spraying, the automatic segmentation algorithm of spraying area based on the determination of hole ratio and Euclidean clustering is studied. For the area with dense features, the point cloud slicing algorithm is used to generate the spray path. For the narrow area, the flexible midline extraction algorithm is proposed. We also discussed the edge extraction algorithm to generate the edge spray path. According to the simulation results of coating thickness, this method can not only ensure the uniformity of coating thickness, but also ensure high spraying efficiency with low paint waste. © 2021 IEEE.

关键词： Clustering algorithms

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Evaluation of surface integrity for ultra-precision machined fused silica surface based on atomic point-defect density

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Journal of Manufacturing Processes 2025年 149卷 917-930页

作者： Dinghuai Yang Linjie Zhao Jian Cheng Qi Liu Zixiao Zhang Hongqin Lei Zican Yang Henan Liu Jinghe Wang Yazhou Sun Mingjun Chen State Key Laboratory of Robotics and System School of Mechatronics Engineering Harbin Institute of Technology Harbin 150001 China Centre for Precision Manufacturing DMEM University of Strathclyde Glasgow G1 1XJ UK Center for Precision Engineering School of Mechatronics Engineering Harbin Institute of Technology Harbin 150001 China

The degree of plasticity and brittleness (DPB) of the material significantly affects the service performance of fused silica manufacturing surfaces in many frontier fields. However, there is still no effective method to quantitatively and non-destructively characterize their DPB, severely restricting the application of fused silica. Herein, atomic manufacturing-induced point defects on fused silica manufacturing surfaces were determined. Based on this, the evolution laws of various types of point defects with the DPB were discussed. Interestingly, it was found that the DPB is closely related to the densities of specific ODCII point defects, whose proportion ( k ) was chosen as the characteristic parameter to judge surface brittle fractures. Additionally, it was discovered that k sharply increased at the material brittle-plastic transition boundary, which was also verified based on the molecular dynamics simulation. Accordingly, whether k is >15 % was proposed as a criterion to judge whether the material has undergone brittle fractures during manufacturing processes. Furthermore, the significant increment of ODCII point defects was found to be the main cause of the obvious increment of k . Moreover, two causes of the significant increment of ODCII point defects were determined. Finally, the effectiveness of the judge criterion in six specific manufacturing cases was verified. Summarily, the study proposes a powerful nondestructive approach to judge the brittle fractures. It could quantitatively and non-destructively characterize the DPB during manufacturing processes. It is also applicable to the quantitative DPB characterization and the early warning detection of fracture breakdown for other brittle silicate materials.

关键词： Fused silica

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Control System Calibration Algorithm for Exoskeleton Under the Individual Specificities of the Operator 2nd

Control System Calibration Algorithm for Exoskeleton Under t...

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2nd International Conference on Modern Problems of robotics, MPoR 2020

作者： Gradetsky, V.G. Ermolov, I.L. Knyazkov, M.M. Semenov, E.A. Sukhanov, A.N. Laboratory of Robotics and Mechatronics Ishlinsky Institute for Problems in Mechanics RAS 119526 Prospect Vernadskogo 101-1 Moscow Russia

ISBN: (纸本)9783030884574

Control approaches for the most modern exoskeleton devices are based on the use of the potentiometric proportional sensors. This allows setting the velocity of the movement of the exoskeleton links, but has significant peculiarities, which are concluded in a large time delay for processing the control signal and increased sensitivity of such sensors, which leads to increased injury risk during control. The use of muscle biopotentials for control of an exoskeleton device also makes it possible to take into account the physiological characteristics of the operator for using the exoskeleton in various areas of human activity. The development of control algorithms of the exoskeleton, along with the use of the activity of human muscle groups’ data, is essential for expanding the functionality of a human-machine system such as the "operator-exoskeleton". The paper considers the interaction of a human and an exoskeleton drive based on mathematical models of a DC motor with a current feedback loop and a muscle duplex. A calibration algorithm is proposed to determine the parameters of the muscle duplex model in order to form a database that corresponds to an individual operator and reflects its individual characteristics. The technique for setting the parameters of the control system in the exoskeleton calibration mode is given. Paper presents the results of experiments with the developed algorithm on full-scale stand, simulating the arm exoskeleton with the electric drive, located in the elbow joint and controlling algorithms based on the electromyogram of the biceps brachii and triceps brachii of the operator. The structure and features of the stand developed in the laboratory of robotics and mechatronics of IPMech RAS are shown. A comparative characteristic of the control quality of the electric drive, which is part of the exoskeleton, with the proposed algorithm in relation to one operator when changing by another one was worked out. At the same time, the following contr

关键词： Calibration

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Singularity-Robust Full-Pose Workspace Control of Space Manipulators with Non-Zero Momentum

TechRxiv

引用

TechRxiv 2023年

作者： Rousso, Patrick Chhabra, Robin Autonomous Space Robotics and Mechatronics Laboratory Carleton University OttawaONK1S 5B6 Canada

We address the end-effector full-pose tracking control problem in free-floating space manipulators, experiencing constant non-zero linear and angular momentum. The aim is to develop an output-tracking (workspace) control law free of singularities due to parameterizing the end-effector motion and being robust against singularities of the input-output decoupling matrix (generalized Jacobian matrix). Space manipulators are modelled as open-chain multi-body systems with single- and multidegree-of-freedom joints, whose kinematics and dynamics are formulated on the Special Euclidean group SE(3). Such systems exhibit conserved (not necessarily zero) total momentum when operating in the free-floating regime, which we use to systematically reduce their dynamical equations by eliminating the base spacecraft’s motion. To avoid parameterizing the end-effector motion, we consider its full pose as the system output and develop a novel feedback linearization technique on the matrix Lie group SE(3) in the reduced phase space of the space manipulator. We then propose an intrinsic feedforward, feedback proportional-integral-derivative workspace controller involving a coordinate-free pose error function on SE(3) and velocity error on its Lie algebra. Using a Lyapunov candidate, this controller is proven to stabilize the end-effector pose to a feasible desired trajectory. The input-output decoupling matrix in the proposed control law can lose rank at some regions of the configuration space;hence, we implement a singularity-robust inverse, derived from the damped least squares method, to avoid impractical joint torques in these regions. The developed controller is implemented on a 7-degree-of-freedom manipulator onboard a spacecraft and its efficacy and robustness are demonstrated trough series of simulations. © 2023, CC BY-NC-SA.

关键词： Controllers

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Noise-Optimized Signal Processing for TENG-Based Touch Sensing Using I2C Integrated Circuits

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IEEE Sensors Journal 2025年

作者： Moger, Gourav Kakim, Alibek Mubarak, Assem Bushanov, Yersaiyn Kalimuldina, Gulnur Yeshmukhametov, Azamat Nazarbayev University Department of Robotics Engineering Astana Kazakhstan Nazarbayev University School of Engineering and Digital Sciences Department of Mechanical and Aerospace Engineering Astana Kazakhstan LLP MiraiTech Astana Kazakhstan Nazarbayev University Institute of Smart Systems and Artificial Intelligence Advanced Robotics and Mechatronics System laboratory Astana Kazakhstan

Triboelectric nanogenerator (TENG) sensors efficiently convert mechanical stimuli into electrical signals, making them well-suited for touch sensing due to their high sensitivity, durability, and self-powered operation. However, conventional signal acquisition methods introduce noise, affecting measurement accuracy. This paper presents a compact, Inter-Integrated Circuit (I2C)-based signal processing circuit designed to enhance signal fidelity while minimizing noise interference. The system’s performance was evaluated by analyzing sensor response across varying contact areas (50 mm² to 576 mm²) and drop heights, demonstrating a consistently high signal-to-noise ratio (SNR) across impact conditions. A high-frequency impact experiment further confirmed the PCB’s ability to distinguish sensor output from noise. Comparison with direct analog acquisition showed a significant enhancement in SNR, validating the PCB’s effectiveness in noise reduction. The system exhibited a rise time of 3.27 milliseconds, ensuring rapid detection of mechanical stimuli. Additionally, the measured latency of 88.9 ms between impact and signal detection falls within acceptable limits for realtime applications. These results establish the proposed PCB-based signal processing method as a practical solution for improving TENG sensor performance in touch-sensing applications requiring high accuracy and noise resilience. The compact, low-power design further enhances its suitability for integration into wearable electronics, interactive surfaces, and space-constrained systems where conventional bulky processing units are impractical. © 2001-2012 IEEE.

关键词： Network coding

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Task-Oriented Stiffness Setting for a Variable Stiffness Hand

Task-Oriented Stiffness Setting for a Variable Stiffness Han...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Ana Elvira H. Martin Ashok M. Sundaram Werner Friedl Virginia Ruiz Garate Máximo A. Roa DLR the Institute of Robotics and Mechatronics German Aerospace Center Wessling Germany Mondragon Unibertsitatea Faculty of Engineering Bilbao Spain Bristol Robotics Laboratory University of the West of England Bristol United Kingdom

The integration of variable stiffness actuators (VSA) in robotic systems endows them with intrinsic flexibility and therefore robustness to unknown disturbances. However, this characteristic presents a challenge: choosing the best intrinsic stiffness setting guaranteeing the required force ap-plication capability while keeping the system as adaptable to uncertainties as possible. This paper proposes a method to set the optimal stiffness for a multi-finger VSA hand to perform a desired manipulation task. The task is generically represented as a force (with unknown magnitude) applied along a reference direction. According to the force application's direction and the hand's kinematic state, the fingers assume a certain role to split the collective force application. We employ the endpoint stiffness ellipsoid to analyze the required finger stiffness to fulfill the task. We evaluate the optimized stiffness settings in a door opening application with an iterative adaption of the stiffness behavior to handle the unknown force requirement. The results show a successful collective behavior of the fingers, where the stiffness setting considers a task-oriented force-adaptability trade-off and effective use of independent VSA fingers.

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Continuous learning with random memory for object detection in robotic applications

Continuous learning with random memory for object detection ...

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2021 International Conference "Nonlinearity, Information and robotics", NIR 2021

作者： Nenakhov, Ivan Mazhitov, Ruslan Artemov, Kirill Zabihifar, SeyedHassan Semochkin, Aleksandr Kolyubin, Sergey ITMO University Biomechatronics and Energy-Efficient Robotics Lab St. Petersburg Russia PJSC Sberbank Sber Robotics Laboratory Moscow Russia Innopolis University Center for Technologies in Robotics and Mechatronics Components Innopolis Russia

ISBN: (纸本)9781665424066

If the robot is to interact with environment designed for humans it has to be able to cope with new objects in it's surrounding, and not only to classify but also effectively localize objects in its reach based on visual sensing. We cannot predict all objects the robot will face. So it needs to learn them while operating, without an external update of software. One of the promising approaches to handle this task is using detectors based on convolution neural networks (CNN) with continuous learning setup. However, there is a well-known problem of catastrophic forgetting (CF) that negatively affects accuracy of neural networks, the main algorithms in object recognition nowadays. Moreover, we need to reach a trade off between training time (because it is unacceptable if the robot trains for hours) and good acccuracy of detection. In this paper we review some of the latest approaches in the field and adapt one of SOtA methods in classification task to detection task. Particularly, we adapt YOLOv5 to work in scenario with continuous learning by adding random memory mechanism from [1] and applying layer freezing in order to increase training speed. We benchmark the proposed method using iCubWorld Transformations dataset and report results with significantly improved metrics and inference speed. © 2021 IEEE.

关键词： Object detection

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Towards Instance Segmentation-Based Litter Collection with Multi-Rotor Aerial Vehicle

Towards Instance Segmentation-Based Litter Collection with M...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Filip Zoric Antonio Franchi Matko Orsag Zdenko Kovacic Chiara Gabellieri Laboratory for Robotics and Intelligent Control Systems (LARICS) at the Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Robotics and Mechatronics Group from the University of Twente Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This paper presents a novel aerial robotics application of instance segmentation-based floating litter collection with a multi-rotor aerial vehicle (MRAV). In the scope of the paper, we present a review of the available datasets for litter detection and segmentation. The reviewed datasets are used to train a Mask-RCNN neural network for instance segmentation. The neural network is off-board deployed on an edge computing device and used for litter position estimation. Based on the estimated litter position, we plan a path based on a quadratic Bezier curve for the litter pickup. We compare different trajectory generation methods for the object pickup. The system is verified in a laboratory environment. Eventually, we present practical considerations and improvements necessary to enable autonomous litter collection with MRAV.

关键词： Instance segmentation Reviews Neural networks Laboratories Estimation Trajectory Aircraft

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