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Development of a Software for Laser-Based Micromachining of Piezoceramic Microactuators 1

AUN/SEED-Net Joint Regional Conference in Transportation, Energy, and mechanical Manufacturing engineering, RCTEMME 2021

作者： Nguyen, Ha Xuan Nguyen, Hung Anh Department of Machine Design and Robotics School of Mechanical Engineering Hanoi University of Science and Technology No. 1 Dai Co Viet Hai Ba Trung Hanoi Viet Nam Department of Mechatronics Engineering Faculty of Mechanical Engineering Thuy Loi University No. 175 Tay Son Dong Da Hanoi Viet Nam

ISBN: (数字)9789811919688

ISBN: (纸本)9789811919671

Laser-based micromachining is often applied to the fabrication of piezoceramic microactuators. In fact, the manual generation of a G-code file for the micromachining of such microactuators is very hard work. In this work, a CAM software for the laser-based micromachining of piezoceramic microactuators was developed. The software was built using C++ and the OpenCV library with Microsoft Visual Studio 9.0. The software has three main classes, including ReadDXF, DrawDXF, and MakeGcode. ReadDXF and DrawDXF were developed to read and display DXF data of the design of fabricated parts in an image for further processing. MakeGcode was built for generating G-code, which is then included in the main program of the NView for running the machine. Robust algorithms were developed so that the software could read complex designs without any failure. Optimization of the toolpath, which can improve machine productivity and lifetime service, was introduced. Results and experimental implementations show that our software can efficiently be used to machine piezoceramic microactuators. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Laser machining Microactuators Piezoceramic

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Torque-Limited Manipulation Planning through Contact by Interleaving Graph Search and Trajectory Optimization

Torque-Limited Manipulation Planning through Contact by Inte...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Ramkumar Natarajan Garrison L.H. Johnston Nabil Simaan Maxim Likhachev Howie Choset The Robotics Institute at Carnegie Mellon University Pittsburgh PA Department of Mechanical Engineering Vanderbilt University

Robots often have to perform manipulation tasks in close proximity to people (Fig 1). As such, it is desirable to use a robot arm that has limited joint torques so as to not injure the nearby person. Unfortunately, these limited torques then limit the payload capability of the arm. By using contact with the environment, robots can expand their reachable workspace that, otherwise, would be inaccessible due to exceeding actuator torque limits. We adapt our recently developed INSAT algorithm [1] to tackle the problem of torque-limited whole arm manipulation planning through contact. INSAT requires no prior over contact mode sequence and no initial template or seed for trajectory optimization. INSAT achieves this by interleaving graph search to explore the manipulator joint configuration space with incremental trajectory optimizations seeded by neighborhood solutions to find a dynamically feasible trajectory through contact. We demonstrate our results on a variety of manipulators and scenarios in simulation. We also experimentally show our planner exploiting robot-environment contact for the pick and place of a payload using a Kinova Gen3 robot. In comparison to the same trajectory running in free space, we experimentally show that the utilization of bracing contacts reduces the overall torque required to execute the trajectory.

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Whale Optimization Algorithm for structural damage detection, localization, and quantification

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Discover Civil engineering 2024年第1期1卷 1-22页

作者： Monteiro, Daniele Kauctz Miguel, Letícia Fleck Fadel Zeni, Gustavo Becker, Tiago de Andrade, Giovanni Souza de Barros, Rodrigo Rodrigues Graduate Program in Civil Engineering (PPGEC) Federal University of Rio Grande Do Sul (UFRGS) Porto Alegre Brazil Department of Mechanical Engineering (DEMEC) Graduate Program in Mechanical Engineering (PROMEC) Graduate Program in Civil Engineering (PPGEC) Federal University of Rio Grande Do Sul (UFRGS) Porto Alegre Brazil Graduate Program in Mining Metallurgy and Materials Engineering (PPGEM) Federal University of Rio Grande Do Sul (UFRGS) Porto Alegre Brazil Department of Mechanical Engineering (DEMEC) Federal University of Rio Grande Do Sul (UFRGS) Porto Alegre Brazil Applied Mechanics Group (GMAp) School of Engineering Federal University of Rio Grande Do Sul (UFRGS) Porto Alegre Brazil

This paper introduces an approach for vibration-based damage detection based on matrix updating aided by the Whale Optimization Algorithm (WOA). The methodology uses the Data-driven Stochastic Subspace Identification (SSI-DATA) technique to determine the modal parameters, which are compared with those obtained from both healthy and damaged conditions of the structure. The methodology’s efficacy is assessed through three distinct steps: numerical simulations, experimental data, and real-world data from a bridge. Initially, numerical analyses are conducted on a cantilever beam, a 10-bar truss, and a Warren truss subjected to environmental vibrations with varying damage cases and noise levels. Subsequently, experimental validations are performed on a test system and in the Z24 Bridge. Results from the computational simulations demonstrate the method’s promise to identify, locate, and quantify single and multiple damage cases, even amidst signal noise, variations in the first vibration mode as minimal as 0.015%, and complex structures with 54 elements. Moreover, the matrix updating method utilizing WOA showcased superior accuracy compared to existing techniques in the literature. In addition, the Z24 Bridge example validated the capability of the presented damage detection method to localize structural damage solely based on natural frequencies.

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Machine Vision Applications in robotics and Automation

Machine Vision Applications in Robotics and Automation

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International Conference on Science Technology engineering and Management (ICONSTEM)

作者： Bharathi GP Kavitha P Laxman Baburao Abhang G. Rathinasabapathi Vipin Sharma T. Sathish Department of Computer and Communication Engineering Sri Sai Ram Institute of Technology Chennai Tamil Nadu India Department of Electrical and Electronics Engineering R.M.K Engineering College Kavaraipettai Tamil Nadu India Department of Automation and Robotics Pravara Rural Engineering College Loni Maharashtra India Department of Mechanical Engineering Panimalar Engineering College Chennai Tamil Nadu India Department of Mechanical Engineering Medi-Caps University Indore Madhya Pradesh Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

The extensive incorporation of machine vision into the fields of robotics and automation in a variety of different ways. The various uses of machine vision and the revolutionary impact it has on the capabilities of robotic systems. This investigation is fueled by improvements in imaging technology and artificial intelligence. In the abstract, major features such as object detection, navigation, and human-robot interaction are discussed in depth. The abstract also demonstrates how machine vision algorithms contribute to enhanced precision, efficiency, and adaptability in automation processes. The purpose of thisis to shed light on the role that machine vision plays in revolutionising industrial automation, collaborative robotics, and autonomous systems by conducting an examination of real-world implementations and case studies. This all-encompassing investigation not only highlights the current status of machine vision applications but also forecasts the future trajectory of this technology, thereby establishing it as a foundational component for the development of robotics and automation in a variety of fields.

关键词： Automation Service robots Navigation Machine vision Imaging Human-robot interaction Object detection

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On the Benefits of Torque Vectoring for Automated Collision Avoidance at the Limits of Handling

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IEEE Transactions on Vehicular Technology 2025年

作者： Bertipaglia, Alberto Tavernini, Davide Montanaro, Umberto Alirezaei, Mohsen Happee, Riender Sorniotti, Aldo Shyrokau, Barys Department of Cognitive Robotics Delft University of Technology Delft2628 CD Netherlands Centre for Automotive Engineering University of Surrey GuildfordGU2 7XH United Kingdom Department of Mechanical Engineering University of Eindhoven Eindhoven5612 AZ Netherlands Departement of Mechanical and Aerospace Engineering Politecnico di Torino Torino10129 Italy

This paper presents a novel approach integrating motion replanning, path tracking and vehicle stability for collision avoidance using nonlinear Model Predictive Contouring Control. Employing torque vectoring capabilities, the proposed controller is able to stabilise the vehicle in evasive manoeuvres at the limit of handling. A nonlinear double-track vehicle model, together with an extended Fiala tyre model, is used to capture the nonlinear coupled longitudinal and lateral dynamics. The optimised control inputs are the steering angle and the four longitudinal wheel forces to minimise the tracking error in safe situations and maximise the vehicle-to-obstacle distance in emergency manoeuvres. These optimised longitudinal forces generate an additional direct yaw moment, enhancing the vehicle’s lateral agility and aiding in obstacle avoidance and stability maintenance. The longitudinal tyre forces are constrained using the tyre friction cycle. The proposed controller has been tested on rapid prototyping hardware to prove real-time capability. In a high-fidelity simulation environment validated with experimental data, our proposed approach successfully avoids obstacles and maintains vehicle stability. It outperforms two baseline controllers: one without torque vectoring and another one without collision avoidance prioritisation. Furthermore, we demonstrate the robustness of the proposed approach to vehicle parameter variations, road friction, perception, and localisation errors. The influence of each variation is statistically assessed to evaluate its impact on the performance, providing guidelines for future controller design. © 1967-2012 IEEE.

关键词： Friction

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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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Using Single Demonstrations to Define Autonomous Manipulation Contact Tasks in Unstructured Environments via Object Affordances

Using Single Demonstrations to Define Autonomous Manipulatio...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Frank Regal Adam Pettinger John A. Duncan Fabian Parra Emmanuel Akita Alex Navarro Mitch Pryor Walker Department of Mechanical Engineering and Texas Robotics The University of Texas at Austin Austin TX USA

Performing a manipulation contact task in an unknown and unstructured environment is still a challenge. Learning from Demonstration (LfD) techniques provide an intuitive means to define difficult-to-model contact tasks, but have attributes that make them undesirable for novice users in uncertain environments. We present a novel end-to-end system that captures a single manipulation task demonstration from an augmented reality (AR) head-mounted display (HMD), computes an affordance primitive (AP) representation of the task, and sends the task parameters to a mobile manipulator for execution in realtime. Using an AR HMD for task demon-stration and APs for task representation has several distinct advantages. AR task demonstration is intuitive, practical, and can be accomplished without requiring sensor installment in the task environment. APs provide a compact and legible task representation, enabling scalability, generalization, and modification of the task without significant data processing overhead. In this effort, we demonstrate system generalization with 10 object manipulation tasks, confirming the computed parameters from all tasks fit within AP tolerances. Secondly, we evaluate a mobile manipulator robot's ability to perform human-demonstrated tasks using AP representation. To increase robustness, we devised and tested four methods to correct for inherent, irreducible position errors in the system. A final study shows the system has a manipulation success rate of 96 % from a single manipulation demonstration on an industrial wheel valve.

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Predictive Stochastic Modeling of mechanically Alloyed Particle Size and Shape

SSRN

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SSRN 2024年

作者： Dwivedi, Anand Prakash Iranmanesh, Emad Sofokleous, Katerina Drakonakis, Vassilis Mashhadzadeh, Amin Hamed Dehaghani, Maryam Zarghami Golman, Boris Spitas, Christos Doumanidis, Haris Mechanical Engineering and Robotics Guangdong Technion Israel Institute of Technology Shantou China Mechanical School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen China AMDM Composites Nicosia Cyprus Department of Mechanical Engineering Nazarbayev University Kazakhstan Department of Chemical and Materials Engineering Nazarbayev University Kazakhstan Department of Mechanical Engineering University of Nottingham Ningbo China Deputy Vice Chancellor Dean of Engineering Wigwe University Nigeria

mechanical alloying of bimetallic materials by ball milling produces particulate products where, aside from internal structure, the size and shape of particles is of importance for various applications. This article introduces two real-time modeling tools for the particle species demographics of size and aspect ratio, their dynamic evolution and dependence on processing conditions: A full physics-based structural simulation, with emphasis on probabilistic representations of impactor collisions, particle assembly and population growth;And a simpler stochastic model of external particle features based on statistical formulations of impact energetics, friction and plastic deformation effects, as well as bonding and fracture transformations of the particles during the process. The models are calibrated and validated experimentally by measurements on laboratory micrographs and literature data in low- and high-energy ball milling of Al-Ni powders at different molar ratios. Their size and shape predictions offer insights to population growth of particles through mechanical alloying phenomena for material design and optimization and process observation for real-time feedback control. © 2024, The Authors. All rights reserved.

关键词： Ball milling

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Development of a Multi-Fingered Soft Gripper Digital Twin for Machine Learning-based Underactuated Control

arXiv

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arXiv 2025年

作者： Yang, Wu-Te Lin, Pei-Chun University of California Berkeley United States Department of Mechanical Engineering National Taiwan University Bio-inspired Robotics Lab Taipei Taiwan

Soft robots, made from compliant materials, exhibit complex dynamics due to their flexibility and high degrees of freedom. Controlling soft robots presents significant challenges, particularly underactuation, where the number of inputs is fewer than the degrees of freedom. This research aims to develop a digital twin for multi-fingered soft grippers to advance the development of underactuation algorithms. The digital twin is designed to capture key effects observed in soft robots, such as nonlinearity, hysteresis, uncertainty, and time-varying phenomena, ensuring it closely replicates the behavior of a real-world soft gripper. Uncertainty is simulated using the Monte Carlo method. With the digital twin, a Q-learning algorithm is preliminarily applied to identify the optimal motion speed that minimizes uncertainty caused by the soft robots. Underactuated motions are successfully simulated within this environment. This digital twin paves the way for advanced machine learning algorithm training. © 2025, CC BY-NC-ND.

关键词： Degrees of freedom (mechanics)

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A Robotic Skin Using Low-density FBGs for Human-robot Interaction

A Robotic Skin Using Low-density FBGs for Human-robot Intera...

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IEEE International Conference on robotics and Biomimetics

作者： Xiyue Dong Chin-Kiu Lam Wei Chen Bohan Yang Yun-Hui Liu Hong Kong Center for Logistics Robotics Hong Kong Department of Mechanical and Automation Engineering T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

In collaborative robotic arms, tactile sensing is crucial for enhancing interaction accuracy and safety. Robotic skins play an vital role in tactile sensing by mimicking the human sense of touch, enabling robots to detect and respond to physical interactions. Fiber Bragg gratings (FBGs), with their high sensitivity, environmental adaptability, and real-time response are increasingly adopted in the design of robotic skin systems. However, current FBG-based research has not resolved the issue of the high-density FBG usage and the large number of optical fibers required, limiting their widespread application in practical scenarios. In this work, we present a design of a soft robotic skin with efficient use of FBGs to estimate the location and magnitude of external forces. Our prototype features a cylindrical shape with a total area of 720 cm 2 and incorporates one optical fiber with 16 evenly spaced FBGs. We optimized the structure through finite element analysis (FEA) and designed experiments to characterize its properties. Using data-driven methods, we achieved root mean square errors (RMSEs) of 4.29 mm and 4.05 degrees in estimating locations along the axial and radial directions, respectively, and 0.17 $N$ for force magnitude. By achieving high sensitivity and an effective area per unit of 50 cm 2 , this approach shows promise for future applications in robotic skin.

关键词： Sensitivity Shape Force Prototypes Soft robotics Robot sensing systems Fiber gratings Skin Sensors Root mean square

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