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检索条件"任意字段=Proceedings of the 3rd International Conference on Mechatronics and Robotics Engineering"

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A Hybrid Nut Sorting System: Utilizing Machine Vision and Augmented Information for Efficient Human-Robot Collaboration

A Hybrid Nut Sorting System: Utilizing Machine Vision and Au...

引用

mechatronics, Control and robotics (ICMCR), international conference on

作者： Kanisorn Sangchai Wongsakorn Adirekkittikun Kevin Vivatanaprasert Methasit Boonpun Wongpakorn Chokthitirath Nutdanai Thipyophat Robotics and Artificial Intelligence Faculty of Engineering International School of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

Efficient sorting and classification of nuts is a critical task in various industries, yet current methods often rely on machine vision systems that inspect each nut individually, making the process time-consuming and inefficient. Additionally, most processes are fully automated, lacking the option for human monitoring or intervention. The novelty of this paper lies in the development of a hybrid nut sorting system that combines machine vision with augmented information to facilitate efficient human-robot collaboration. Unlike traditional fully automated systems that exclude human involvement, our approach integrates a projector-based visual aid to provide real-time, easily interpretable information for manual or semi-automated sorting. Additionally, the system incorporates a CoreXY robot path and mechanism, enabling collaboration between humans and robots. The detection system consistently identifies nuts of different sizes with reliable accuracy, particularly for simultaneous multi-object detection compared to singular detection methods. As a hybrid sorting system, our solution also allows humans to manually sort nuts at a faster rate than the machine while utilizing the system's assistance.

关键词： Visualization Accuracy Machine vision Human-robot interaction Collaboration Size measurement Path planning Classification algorithms Reliability Sorting

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Implementation of an Embedded Electronic Control System for a Functional Prosthetic Hand

Implementation of an Embedded Electronic Control System for ...

引用

mechatronics, Control and robotics (ICMCR), international conference on

作者： Magno Parra Victoria E. Abarca Dante A. Elias Biomechanics and Applied Robotics Research Laboratory Pontificia Universidad Católica del Perú Lima Peru

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

The advancement of electronics enables the development of more complex functional prosthetics with more capabilities and functionality. The prosthetics currently developed do not leave the laboratory environment due to their complexity or the requirement to operate in conjunction with laboratory computing equipment. Therefore, it is essential to develop prosthetics that can operate outside of the laboratory environment while maintaining maximum functionality. Consequently, an electronic control system is developed that can be embedded in a functional prosthetic hand, which is then trained in real-time through electromyography (EMG) using a classification algorithm based on machine learning. The system allows the prosthetic hand to assume six different positions and be controlled by electromyography, recognizing flexion and extension movements of the wrist. This results in a control system that can be fully embedded in the prosthetic hand, with an appropriate weight and size to maintain the aesthetics and functionality of the prosthesis.

关键词： Wrist mechatronics Laboratories Control systems Robot sensing systems Electromyography Real-time systems Classification algorithms Time factors Prosthetic hand

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Improving Robotic Arms Through Natural Language Processing, Computer Vision, and Edge Computing

Improving Robotic Arms Through Natural Language Processing, ...

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mechatronics, Control and robotics (ICMCR), international conference on

作者： Pascal Sikorski Kaleb Yu Lucy Billadeau Flavio Esposito Hadi AliAkbarpour Madi Babaias Undergraduate Research Assistant Computer Science Department Saint Louis University Saint Louis USA Undergraduate Research Assistant Aerospace & Mechanical Engineering Department Saint Louis University Saint Louis USA Associate Professor Computer Science Department Saint Louis University Saint Louis USA Assistant Professor Computer Science Department Saint Louis University Saint Louis USA CBL Assistant Professor of Robotics Aerospace & Mechanical Engineering Department Saint Louis University Saint Louis USA

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This paper introduces a prototype for a new approach to assistive robotics, integrating edge computing with Natural Language Processing (NLP) and computer vision to enhance the interaction between humans and robotic systems. Our proof of concept demonstrates the feasibility of using large language models (LLMs) and vision systems in tandem for interpreting and executing complex commands conveyed through natural language. This integration aims to improve the intuitiveness and accessibility of assistive robotic systems, making them more adaptable to the nuanced needs of users with disabilities. By leveraging the capabilities of edge computing, our system has the potential to minimize latency and support offline capability, enhancing the autonomy and responsiveness of assistive robots. Experimental results from our implementation on a robotic arm show promising outcomes in terms of accurate intent interpretation and object manipulation based on verbal commands. This research lays the groundwork for future developments in assistive robotics, focusing on creating highly responsive, user-centric systems that can significantly improve the quality of life for individuals with disabilities. For video demonstrations and source code, please refer to: https://***/EnhancedArmEdgeNLP.

关键词： Computer vision mechatronics Source coding Machine vision Large language models Prototypes Focusing Manipulators Natural language processing Edge computing

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Design and Implementation of a Backstepping PID Controller for Trajectory Tracking of Differential Drive-Wheeled Mobile Robot 3rd

Design and Implementation of a Backstepping PID Controller f...

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3rd international conference on Advances in Information and Communication Technology, ICTA 2024

作者： Tu, Duong Dinh Phuong, Ho Sy Luong, Tran Duc Van Chuong, Le Van Thanh, Vu Phuoc, Le Ngoc Department of Automatic Control Institute of Engineering and Technology Vinh University Nghe An Province Vinh City Viet Nam

ISBN: (纸本)9783031809422

Trajectory tracking is a critical issue in the field of mobile robotics. This paper aims to design and implement a backstepping PID controller for trajectory tracking of a differential drive-wheeled mobile robot, evaluating the practical performance of this controller. Initially, we design and construct the robot. We then develop detailed kinematic and dynamic models for the robot and create a controller that integrates backstepping and PID techniques based on these models. A simulation model based on the actual parameters of the robot is subsequently developed. Finally, experiments are conducted to validate the effectiveness of the proposed controller. The experimental process involved a circular trajectory with a radius of 1.5 m, resulting in minimal orbital errors ranging from –0.01 m to 0.01 m. These results confirm the effectiveness of the backstepping PID controller, demonstrating its practical applicability for mobile robot trajectory tracking. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Three term control systems

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Deployment of Large Language Models to Control Mobile Robots at the Edge

Deployment of Large Language Models to Control Mobile Robots...

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mechatronics, Control and robotics (ICMCR), international conference on

作者： Pascal Sikorski Leendert Schrader Kaleb Yu Lucy Billadeau Jinka Meenakshi Naveena Mutharasan Flavio Esposito Hadi AliAkbarpour Madi Babaias Computer Science Department Saint Louis University Saint Louis USA Aerospace & Mechanical Engineering Department Saint Louis University Saint Louis USA

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This paper investigates the possibility of intuitive human-robot interaction through the application of Natural Language Processing (NLP) and Large Language Models (LLMs) in mobile robotics. This work aims to explore the feasibility of using these technologies for edge-based deployment, where traditional cloud dependencies are eliminated. The study specifically contrasts the performance of GPT-4-Turbo, which requires cloud connectivity, with an offline-capable, quantized version of LLaMA 2 (LLaMA 2-7B.Q5 K M). These results show that GPT-4-Turbo delivers superior performance in interpreting and executing complex commands accurately, whereas LLaMA 2 exhibits significant limitations in consistency and reliability of command execution. Communication between the control computer and the mobile robot is established via a Raspberry Pi Pico W, which wirelessly receives commands from the computer without internet dependency and transmits them through a wired connection to the robot's Arduino controller. This study highlights the potential and challenges of implementing LLMs and NLP at the edge, providing groundwork for future research into fully autonomous and network-independent robotic systems. For video demonstrations and source code, please refer to: https://***/MobileRobotGPT4LLaMA2024.

关键词： Cloud computing mechatronics Large language models Source coding Human-robot interaction Natural language processing Software reliability Mobile robots Edge computing

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proceedings of the 3rd international conference on mechatronics and Intelligent robotics, ICMIR 2019

Proceedings of the 3rd International Conference on Mechatron...

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3rd international conference on mechatronics and Intelligent robotics, ICMIR 2019

The proceedings contain 107 papers. The topics discussed include: analytical analysis of horse riding machine based on ergonomics;research and construction of the online pesticide information center and discovery platform based on web crawler;force feedback based on magnetorheological fluid;implementation of FPGA-based controller in automatic control system platform for launch site;research on in-situ measurement simulation test of inertia of flywheel simulator by SimMechanics;construction and application of a static load performance testing platform for truck-mounted drilling rigs;design and implementation of automatic invigilation functions using the embedded technology;and simulation analysis of the effect of turning radius on the running safety of piggyback transportation vehicle system

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Latent 3D Scene Graph with Aligned Visual-Language Perception for Object-Goal Navigation

Latent 3D Scene Graph with Aligned Visual-Language Perceptio...

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mechatronics, Control and robotics (ICMCR), international conference on

作者： Jianwei Zhang Kang Zhou Junjie Yang Xiaojian Li College of Engineering Southern University of Science and Technology Shen Zhen China School of Computer Science City University of Hong Kong Hong Kong China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shen Zhen China

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

Object-goal navigation requires agents to accurately locate and navigate to specified target objects in complex indoor environments. Existing methods primarily rely on single visual observations or simple semantic matching, making it difficult to effectively understand 3D scene relationships between target objects, which leads to inefficient path planning during navigation. Furthermore, the feature discrepancy between visual and language modalities poses challenges for accurate target identification. To address these issues, we propose Latent 3D Scene Graph with Aligned Visual-Language Perception (LSGAP), a novel approach that explicitly models 3D scene relationships between objects through depth perception and latent 3D scene graph construction. Meanwhile, we leverage multimodal pretraining strategies to achieve effective visual-language feature alignment, enhancing the model's target recognition capabilities. This end-to-end architectural design improves spatial cognition ability and enables more efficient navigation decision-making. We conduct extensive experimental evaluations in the AI2THOR interactive environment to validate the effectiveness of our navigator.

关键词： Visualization Solid modeling Three-dimensional displays Systematics Navigation Target recognition Semantics Indoor environment Standards Robots

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Industrial Ahu Control Improvements using Fuzzy Logic for Energy Efficiency and Comfort

Industrial Ahu Control Improvements using Fuzzy Logic for En...

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mechatronics, Control and robotics (ICMCR), international conference on

作者： Syahmirullah Sulaiman Muhammad Rusydi Muhammad Razif Alan Tan Thiam Swee Hairulazwan Hashim Hikma Shabani Faculty of Engineering Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia iETCO EnergyCap Sdn Bhd Selangor Malaysia School of Electrical and Communications Engineering Papua New Guinea University of Technology Lae Papua New Guinea

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This study focuses on how fuzzy logic control can improve the efficiency and performance of Air Handling Unit (AHU) systems. Traditional methods of controlling AHUs, like fixed-frequency operation, often waste energy, cause unstable temperatures, and wear out equipment faster. To solve these problems, a fuzzy logic controller was designed to regulate motor frequency and motorized valve positions based on real-time inputs from Supply Air Temperature (SAT) and Return Air Temperature (RAT). The controller used Modbus communication to exchange data between Variable Frequency Drive (VFD). The system was tested over 21 days at a commercial building, comparing its performance to fixed-frequency settings between 40 Hz to 50 Hz configuration. The results showed that fuzzy logic control could reduce energy usage by up to 38% and stable temperatures. This research shows that fuzzy logic can improve energy efficiency and comfort in HVAC systems, making it a useful solution for modern building management.

关键词： Fuzzy logic HVAC Buildings Variable speed drives Motors Valves Energy efficiency Real-time systems Reliability Frequency control

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Three-Dimensional Trajectory Planning for Quadrotor UAV Based on Simplified PSO Algorithm 3rd

Three-Dimensional Trajectory Planning for Quadrotor UAV Base...

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3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Yin, Ruhui Jiang, Han Shu, Zilin Ren, Ziang Lin, Qinghao Huang, Zixin School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430200 China Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Nankai University Tianjin300350 China

ISBN: (纸本)9789819624676

Aiming to address the requirements of Quadrotor Unmanned Aerial Vehicle (QUAV) for conducting mission cruises in three-dimensional complex environments, this paper introduces an optimization algorithm for trajectory planning. By analyzing the motion of the QUAV, the dynamics model is established, along with the constraint model for its flight trajectory. Based on the basic Particle Swarm Optimization (PSO) algorithm, simplified Particle Swarm Optimization (sPSO) removes the particle velocity term from the evolution equation. This adjustment helps prevent slower convergence and lower accuracy in the later stages, which can occur due to the dispersion of particles caused by the particle velocity term. The trajectory is smoothed by using the Minimum Snap principle to ensure that it meets the flight constraints of the QUAV. The simulation results demonstrate that the sPSO algorithm is effective and feasible for application in QUAV three-dimensional trajectory planning. In comparison to the PSO algorithm, the trajectory is more optimal, and the convergence accuracy is higher. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Particle swarm optimization (PSO)

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Novel 6D Pose Estimation for Pick-and-Place Tasks using Model-based Learning

Novel 6D Pose Estimation for Pick-and-Place Tasks using Mode...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Logesh G S. Vinoth Nagarajan Pitchandi A.G. Karthikeyan Computer Science and Business Systems Bannari Amman Institute of Technology Sathyamangalam India Department of Mechatronics Akshaya College of Engineering and Technology Coimbatore India Department of Mechatronics Bannari Amman Institute of Technology Sathyamangalam India School of Mechanical Engineering REVA University Bangalore India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

The paper discusses the problem of creating an autonomous SCARA robot that can precisely carry out pick-and-place operations in unstructured settings. The suggested method combines computer vision and deep learning algorithms to provide accurate 6D pose estimation and reliable object detection. Combining YOLOv8 for object detection, hand-eye calibration for precise transformation to robot coordinates, and Principal Component Analysis (PCA) for orientation estimation within the generated point cloud, a novel method for estimating object pose is presented. Monocular depth estimation techniques are used to extract depth information from RGB images to create point clouds. The results demonstrate the potential of combining advanced algorithms with user-friendly design for robotics automation, showing notable gains in pose estimation accuracy and task execution efficiency.

关键词： Point cloud compression Accuracy Service robots Robot kinematics Pose estimation Object detection Manuals Calibration Reliability Principal component analysis

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