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American control Conference (ACC)

作者： Bolun Dai Heming Huang Prashanth Krishnamurthy Farshad Khorrami Electrical & Computer Engineering Department Control/Robotics Research Laboratory Tandon School of Engineering New York University Brooklyn NY

control barrier functions (CBFs) have been widely used for synthesizing controllers in safety-critical applications. When used as a safety filter, a CBF provides a simple and computationally efficient way to obtain safe controls from a possibly unsafe performance controller. Despite its conceptual simplicity, constructing a valid CBF is well known to be challenging, especially for high-relative degree systems under nonconvex constraints. Recently, work has been done to learn a valid CBF from data based on a handcrafted CBF (HCBF). Even though the HCBF gives a good initialization point, it still requires a large amount of data to train the CBF network. In this work, we propose a new method to learn more efficiently from the collected data through a novel prioritized data sampling strategy. A priority score is computed from the loss value of each data point. Then, a probability distribution based on the priority score of the data points is used to sample data and update the learned CBF. Using our proposed approach, we can learn a valid CBF that recovers a larger portion of the true safe set using a smaller amount of data. The effectiveness of our method is demonstrated in simulation on a two-link arm.

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SIT-Net: Surgical Image Translation Network Using a Generative Adversarial Method with Visual Feature Disentanglement

SIT-Net: Surgical Image Translation Network Using a Generati...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Guo, Yuhao Zhou, Tiancheng Chi, Wenzheng Zhou, Feng Qi, Peng Li, Ling Sun, Lining Lu, Bo Soochow University Robotics and Microsystems Center School of Mechanical and Electric Engineering Suzhou215021 China Soochow University First Affiliated Hospital Department of Orthopedics Suzhou215021 China Tongji University Department of Control Science and Engineering Shanghai China Suzhou Ultimage Health Technology Co. Ltd. China

ISBN: (纸本)9798350327182

With flourishing advancements of surgical robots and learning-driven algorithms, surgical automation that enables robots with autonomous functions for certain subtasks by learning experts' skills is attracting tremendous attention. To facilitate its development, introducing a high-quality surgical image translation method from current scenes to desired domains can not only augment the data for model training but also alleviate the problems that may frequently encounter using traditional approaches, like visual blurs or incomplete instrument generations. To this end, we propose a new surgical image generation method called Surgical Image Translation Network (SIT-Net). Considering complex features entangled within surgical images, a novel generator that leverages tool masks to disentangle the foreground and background characteristics is proposed. Besides, to retain the completeness of instruments, a novel loss function that can preserve tools' features is introduced to further supervise the model training process. We extensively evaluated our method in terms of the visual appearance of translated images and adopted an evaluation indicator Fréchet Inception Distance (FID) to verify whether the generated images are close to the target domain or not. Both the qualitative and quantitative outcomes demonstrate that our SIT-Net is superior to the traditional approach regarding surgical image translation and generation in desired scenes. © 2023 IEEE.

关键词： Robotic surgery

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MateRobot: Material Recognition in Wearable robotics for People with Visual Impairments

MateRobot: Material Recognition in Wearable Robotics for Peo...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Junwei Zheng Jiaming Zhang Kailun Yang Kunyu Peng Rainer Stiefelhagen Institute for Robotics and Anthropomatics Karlsruhe Institute of Technology Karlsruhe Germany Department of Engineering Science University of Oxford UK School of Robotics and the National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

People with Visual Impairments (PVI) typically recognize objects through haptic perception. Knowing objects and materials before touching is desired by the target users but under-explored in the field of human-centered robotics. To fill this gap, in this work, a wearable vision-based robotic system, MATERobot, is established for PVI to recognize materials and object categories beforehand. To address the computational constraints of mobile platforms, we propose a lightweight yet accurate model MATEViT to perform pixel-wise semantic segmentation, simultaneously recognizing both objects and materials. Our methods achieve respective 40.2% and 51.1% of mIoU on COCOStuff-10K and DMS datasets, surpassing the previous method with +5.7% and +7.0% gains. Moreover, on the field test with participants, our wearable system reaches a score of 28 in the NASA-Task Load Index, indicating low cognitive demands and ease of use. Our MATERobot demonstrates the feasibility of recognizing material property through visual cues and offers a promising step towards improving the functionality of wearable robots for PVI. The source code has been made publicly available at MATERobot.

关键词： Visualization Source coding Semantic segmentation Visual impairment Semantics Wearable robots Mobile applications

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Pulsating Fluidic Sensor for Sensing of Location, Pressure and Contact Area

Pulsating Fluidic Sensor for Sensing of Location, Pressure a...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Joanna Jones Marco Pontin Dana D. Damian Department of Automatic Control and Systems Engineering Sheffield Biomedical Robotics Laboratory University of Sheffield United Kingdom Sheffield Robotics University of Sheffield UK Insigneo Institute for in Silico Medicine University of Sheffield UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Designing information-rich and space-efficient sensors is a key challenge for soft robotics, and crucial for the development of safe soft robots. Sensing and understanding the environmental interactions with a minimal footprint is especially important in the medical context, where portability and unhindered patient/user movement is a priority, to move towards personalized and decentralized healthcare solutions. In this work, a pulsating fluidic soft sensor (PFS) capable of determining location, pressure and contact area of press events is shown. The sensor relies on spatio-temporal resistance changes driven by a pulsating conductive fluid. The sensor demonstrates good repeatability and distinction of single and multiple press events, detecting single indents of sizes greater than 1 cm, forces larger than 2 N, and various locations across the sensor, as well as multiple indents spaced 2 cm apart. Furthermore, the sensor is demonstrated in two applications to detect foot placement and grip location. Overall, the sensor represents an improvement towards minimizing electronic hardware, and cost of the sensing solution, without sacrificing the richness of the sensing information in the field of soft fluidic sensors.

关键词： Presses Fluids Soft sensors Medical services Soft robotics Robot sensing systems Hardware

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Model Predictive control with Model Error Compensation by Koopman Approach 48

Model Predictive Control with Model Error Compensation by Ko...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Kanai, Masaki Yamakita, Masaki R&d Group Hitachi Ltd. Controls and Robotics Innovation Center Ibaraki Japan Tokyo Institute of Technology Department of Systems and Control Engineering Tokyo Japan

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

This study proposes a method for high-performance model predictive control (MPC) by using a lifted bilinear model error model (MEM) based on the Koopman approach to compensate for errors in the prediction model. In MPC, more accurate prediction models can be expected to provide better control performance for the real plant. However, there often exist modeling errors in the prediction model, which may prevent MPC from achieving good performance. In this study, we identify the errors in the nominal model as an MEM, and formulate an MPC that integrates the nominal model and the MEM into an "error-compensated model"as a prediction model. We model the MEM with a lifted bilinear model that can represent nonlinear characteristics based on Koopman's theory. In addition, an efficient linear MPC algorithm is constructed by linearizing the MEM while maintaining high prediction accuracy. Numerical simulations demonstrate the effectiveness of the proposed method. © 2022 IEEE.

关键词： Model predictive control

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ReFlow6D: Refraction-Guided Transparent Object 6D Pose Estimation via Intermediate Representation Learning

arXiv

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arXiv 2024年

作者： Gupta, Hrishikesh Thalhammer, Stefan Weibel, Jean-Baptiste Haberl, Alexander Vincze, Markus Vision for Robotics Laboratory Automation and Control Institute TU Wien Austria Industrial Engineering Department UAS Technikum Vienna TU Wien Austria

Transparent objects are ubiquitous in daily life, making their perception and robotics manipulation important. However, they present a major challenge due to their distinct refractive and reflective properties when it comes to accurately estimating the 6D pose. To solve this, we present ReFlow6D, a novel method for transparent object 6D pose estimation that harnesses the refractive-intermediate representation. Unlike conventional approaches, our method leverages a feature space impervious to changes in RGB image space and independent of depth information. Drawing inspiration from image matting, we model the deformation of the light path through transparent objects, yielding a unique object-specific intermediate representation guided by light refraction that is independent of the environment in which objects are observed. By integrating these intermediate features into the pose estimation network, we show that ReFlow6D achieves precise 6D pose estimation of transparent objects, using only RGB images as input. Our method further introduces a novel transparent object compositing loss, fostering the generation of superior refractive-intermediate features. Empirical evaluations show that our approach significantly outperforms state-of-the-art methods on TOD and Trans32K-6D datasets. Robot grasping experiments further demonstrate that ReFlow6D’s pose estimation accuracy effectively translates to real-world robotics task. The source code is available at: https://***/StoicGilgamesh/ReFlow6D and https://***/StoicGilgamesh/matting *** Codes 68T45 © 2024, CC BY-NC-SA.

关键词： Light refraction

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Recursive Model-agnostic Inverse Dynamics of Serial Soft-Rigid Robots

arXiv

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arXiv 2024年

作者： Pustina, Pietro Santina, Cosimo Della De Luca, Alessandro Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Cognitive Robotics Delft University of Technology Delft Netherlands Oberpfaffenhofen Germany

robotics is shifting from rigid, articulated systems to more sophisticated and heterogeneous mechanical structures. Soft robots, for example, have continuously deformable elements capable of large deformations. The flourishing of control techniques developed for this class of systems is fueling the need of efficient procedures for evaluating their inverse dynamics (ID), which is challenging due to the complex and mixed nature of these systems. As of today, no single ID algorithm can describe the behavior of generic (combinations of) models of soft robots. We address this challenge for generic series-like interconnections of possibly soft structures that may require heterogeneous modeling techniques. Our proposed algorithm requires as input a purely geometric description (forward-kinematics-like) of the mapping from configuration space to deformation space. With this information only, the complete equations of motion can be given an exact recursive structure which is essentially independent from (or ‘agnostic’ to) the underlying reduced-order kinematic modeling techniques. We achieve this goal by exploiting Kane’s method to manipulate the equations of motion, showing then their recursive structure. The resulting ID algorithms have optimal computational complexity within the proposed setting, i.e., linear in the number of distinct modules. Further, a variation of the algorithm is introduced that can evaluate the generalized mass matrix without increasing computation costs. We showcase the applicability of this method to robot models involving a mixture of rigid and soft elements, described via possibly heterogeneous reduced order models (ROMs), such as Volumetric FEM, Cosserat strain-based, and volume-preserving deformation primitives. None of these systems can be handled using existing ID techniques. © 2024, CC BY.

关键词： Inverse problems

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A control Strategy for Bidirectional Buck Converter with Combining Continuous and Active Discontinuous Conducting Modes

A Control Strategy for Bidirectional Buck Converter with Com...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Evgeniy Stolyarov Maxim Lashkevich Egor Kulik Yousef Ali Galina Demidova Alecksey Anuchin Department of Electric Drives Moscow Power Engineering Institute Moscow Russia Faculty of Control System and Robotics ITMO University Saint Petersburg Russia

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

The hybrid electric powertrains can utilize bidirectional buck converters to charge the battery while driving and discharge it when extra power is required. In order to increase the power density, the wide-bandgap switches should be used. These switches have bidirectional conductivity mode as they are metal-oxide-semiconductor field-effect transistors (MOSFET) and the utilization of the freewheeling diode is undesirable due to high voltage drop across it and much higher losses in conducting mode. This paper proposes the combined control strategy which implements continuous conducting mode at high and active discontinuous conducting mode at low currents. The use of model predictive control allows to minimize the conducting losses by means of reverse conductivity mode of the switches. The paper provides derivation of the combined control strategy. Then, the simulation results show the effectiveness of the proposed method. Finally, the simulation was performed with various errors in the definition of the system parameters.

关键词： Power system measurements MOSFET Buck converters Density measurement Mechanical power transmission Conductivity control systems

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Design and Implementation of Pick and Place Manipulation System for Industrial Automation

Design and Implementation of Pick and Place Manipulation Sys...

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2021 International Conference on Artificial Intelligence and Mechatronics Systems, AIMS 2021

作者： Naeem, Mehreen Aslam, Shoaib Suhaib, Muhammad Gul, Seemab Murtaza, Zeeshan Khan, Muhammad Jawad National University of Science and Technology Department of Robotics and Intelliegnt Machine Engineering Pakistan University of Engineering and Technology Lahore Department of Mechatronics and Control Engineering Pakistan

ISBN: (纸本)9781665424820

This work presents an autonomous pick and pack system for industrial applications consisting of a 4-DOF (degree-of-freedom) robotic manipulator and the vision perception. The system is capable to detect and capture products/materials from a production line and place them in a packaging box one at a time. The final placement of the object in the box is carried out with the desired orientation. The adopted configuration of the manipulator is RRPR equipped with an electromagnetic end-effector. Inverse kinematics approach is used to determine the end-effector motion sequence in order to reach the desired locations within the workspace. The manipulator is equipped with Feetech SC servo motor with built-in PID controller at each joint to achieve precise motion of joint angles. An RGB camera is mounted right above the conveyer belt to capture the region of interest in the environment. Captured image is further preprocessed by image processing techniques. Region properties is used to extract the orientation of the object. Arduino Mega 2560 is used as a control board for motors and an interface with the PC. A graphical user interface (GUI) is developed in MATLAB to monitor and control the end-to-end pick and pack system featuring both manual and automatic modes. © 2021 IEEE.

关键词： End effectors

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Reviewing Fault Diagnosis Methods in Electric Drives: Power Subsystem and Electrical Machine 24

Reviewing Fault Diagnosis Methods in Electric Drives: Power ...

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24th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2023

作者： Demidova, Galina Chen, Hao Li, Yibin Lukichev, Dmitry Anuchin, Alecksey Itmo University Faculty of Control System and Robotics Saint-Petersburg Russia School of Electrical and Power Engineering China University of Mining and Technology Xuzhou China Institute of Marine Science and Technology Shandong University Shandong China Moscow Power Engineering Institute Department of Electric Drives Moscow Russia

ISBN: (纸本)9798350336870

This paper provides a review of popular fault diagnosis methods in the power subsystem and electrical machine of electric drives. The review aims to explore the different approaches used to detect faults in these components and the most common types of faults encountered in electric drives. The paper first provides an overview of the power subsystem and electrical machine and their respective functions within the electric drive system. It then proceeds to discuss the different types of faults that can occur in these components, including overvoltage, undervoltage, overcurrent, and short circuits. The review evaluates the various fault diagnosis methods available for these components, including model-based, signal-based, and artificial intelligence-based approaches. Model-based approaches use mathematical models of the system to detect and diagnose faults. Signal-based approaches rely on the analysis of measured signals to detect changes in system behavior that indicate a fault. Artificial intelligence-based approaches use machine learning algorithms to identify patterns in data and detect faults. Model-based approaches are highly accurate but can be computationally intensive. Signal-based approaches are less computationally intensive but may be less accurate in certain situations. Artificial intelligence-based approaches are versatile but require significant amounts of data for training. This review provides a comprehensive overview of the current state-of-the-art in fault diagnosis methods for the power subsystem and electrical machine of electric drives. The review concludes by suggesting potential areas for future research to further improve the accuracy and efficiency of fault diagnosis methods for electric drives. © 2023 IEEE.

关键词： Failure analysis

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