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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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Future of AI-Driven Surgical robotics

Future of AI-Driven Surgical Robotics

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Disruptive Technologies (ICDT), international conference on

作者： Shivanshi Nigam Madhuri Gupta Sonali Srivastava Mohammad Asad Khan Sameer Malik Richa Chaturvedi School of Computer Science Engineering and Technology Bennett University Greater Noida India Samsara San Francisco California USA University at buffalo New York USA

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

Artificial Intelligence (AI)-driven surgical robotics is revolutionizing modern medicine by enhancing precision, reducing human error, and enabling minimally invasive procedures with improved patient outcomes. AI-powered robots leverage real-time decision-making, adaptive control, and autonomous task execution, surpassing traditional surgical methods. With applications across various specialties, AI-driven systems like the Da Vinci Surgical System and Smart Tissue Autonomous Robot (STAR) are already reshaping surgeries, offering better precision and reduced recovery times. This paper explores the motivations behind integrating AI into surgical robotics, its current applications, and the potential for fully autonomous surgeries. Despite challenges such as data quality, high costs, and regulatory barriers, AI-driven surgical robotics holds promise for significantly improving patient care, particularly in underserved regions. By surveying existing systems, AI techniques, and emerging trends, this research highlights the future of surgery, offering insights into the transformative role AI will play in healthcare's evolution.

关键词： Medical robotics Minimally invasive surgery Costs Stars Precision engineering Medical services Machine learning Market research Real-time systems Artificial intelligence

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Solar-Powered Smart Wheelchair with Voice controller for Physically Challenged People

Solar-Powered Smart Wheelchair with Voice Controller for Phy...

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Advancements in Electrical, Electronics, Communication, Computing and automation (ICAECA), international conference on

作者： M. Karthik G. Hemalatha L. Sreevidya R. Deepalakshmi K Premalatha Department of Electrical and Electronics Engineering SRM Madurai College for Engineering and Technology Tamil Nadu India Department of Robotics and Automation Sri Ramakrishna Engineering College Coimbatore Tamil Nadu India Department of Electrical and Electronics Engineering V.S.B College of Engineering Technical Campus Coimbatore Tamil Nadu India Department of Computer Science Engineering SRM Madurai College for Engineering and Technology Tamil Nadu India Department of Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

It is challenging for those with strong mental faculties but physical disabilities to get around in a conventional hand-powered wheelchair. This project will enable any existing wheelchair to have an inexpensive assembly that enables a smart motion automation system that can be controlled by speech recognition on a smartphone. Continuous operation is guaranteed by the dual-charging system, which also offers longer mobility without the need for frequent recharging and independence from external power outlets. This enables users to adjust to varying conditions by depending on solar power during the day and switching to battery charging when solar energy is scarce. The main concept is a smartphone with built-in Bluetooth connectivity and the Android operating *** the distribution of the application we have developed, the goal of our project may be extended to other mobile devices that run Android software. The second main component of our system design is the microprocessor, which drives the wheelchair's dc motor in different directions. The wheelchair may now travel in a variety of directions thanks to this. The suggested model operates autonomously and on its own.

关键词： automation Gears Navigation Wheelchairs Operating systems Wheels Solar energy DC motors Mobile handsets Telecommunication computing

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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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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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Flexible Target Grasping Strategy of Industrial Robot Based on Eye-in-Hand 3D Machine Vision

Flexible Target Grasping Strategy of Industrial Robot Based ...

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robotics and Technologies for Industrial automation (ROBOTHIA), IEEE international conference on

作者： Zhang XiaoYang Muhammad Azmi Ayub Fazlina Ahmat Ruslan Shuzlina Abdul-Rahman Sukarnur Che Abdullah College of Engineering UiTM Shah Alam Shah Alam Selangor Malaysia College of Computing Informatics and Media UiTM Shah Alam Shah Alam Selangor Malaysia

ISBN: (数字)9798350356755

ISBN: (纸本)9798350356762

Object grasping is the most common application direction of robots, and machine vision technology is also the most common application of grasping. With the deepening of the research of machine vision technology, the initial application in static target capture has gradually expanded to some moving target tracking and capture. Estimating and predicting the moving state of a target by detecting its position is a common method for obtaining a stable moving target. Once the target motion changes position due to unpredictable interference, the original predicted position will be invalid. Therefore, it is necessary to constantly locate and track the target and judge the deviation, so as to constantly approach the new target position and finally achieve the capture. In this paper, we utilize the open-source Robot Operating System (ROS) platform to investigate dynamic grasping strategies based on visual feedback. In this paper, we use ROS, based on UR5 robot arm and RealSense D435i camera, based on the eye-in-hand mode, to study the dynamic grasping strategy based on visual feedback. A visual feedback control strategy based on fixation approximation is designed to enable the grasping of moving targets on a conveyor belt. Finally, it is verified that the machine vision-driven feedback capturing algorithm substantially meets the practical application requirements of engineering, demonstrating high feasibility and accuracy.

关键词： Visualization Target tracking Three-dimensional displays Service robots Machine vision Operating systems Robot vision systems Grasping Object detection Industrial robots

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Automated Crop Harvesting with robotics Using AI

Automated Crop Harvesting with Robotics Using AI

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Device Intelligence, Computing and Communication Technologies, (DICCT), international conference on

作者： Kumar P Sangathtamil S Sadiq Peer Mohamed K Department of CSE Rajalakshmi Engineering College Chennai India Department of CSE REC Chennai India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

“Automated Crop Harvesting using robotics and AI” research may truly change the future of modern farming. New Robot Systems Integrated with Smarter Artificial Intelligence So the objective for making self-operating harvesters that can move around fields and find ripe crops using advanced machine vision and executing selective harvesting accurately. Among them, the project on real-time data from Using environmental sensors and AI-driven predictive analytics, the system hopes to improve harvesting. operations, increase crop yield, reduce waste. Innovation addresses pivotal issues such as labour Shortages and high operational costs while promoting sustainable farming practices. Ultimately, this project It works toward making farming better, ensuring that food is produced in a more reliable and efficient way. Also, this project considers how these technologies can work with farm management systems to Provides full monitoring and control. The all-inclusive method not only makes immediate harvesting better. Tasks and also helps with long-term farming plans and managing resources. By encouraging with new developments in robots and AI, the project aims to create better ways in farming technology, opening the This is the way forward to smart farming, the future.

关键词： Temperature sensors Program processors Accuracy Crops Robot sensing systems Manipulators Sensor systems Real-time systems Artificial intelligence Farming

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Design and testing of Hybrid Slime Mold Algorithm for Real-Time Adaptive Mobile Robot Path Planning in Dynamic Environments

Design and testing of Hybrid Slime Mold Algorithm for Real-T...

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Advancement in Computation & Computer Technologies (InCACCT), international conference on

作者： Sachin Gupta Shivali Gupta Shaik Mohammed Raith Anand Kumar Salil Bharany Vishnu Kant Ch.Sandeep Department of Robotics and Control Engineering School of Electronics and Control Engineering Lovely Professional University Phagwara India Department of Chemistry School of Chemical Engineering and Physical Sciences Lovely Professional University Phagwara India Department of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Chitkara University Institute of Engineering and Technology Chitkara University Rajpura India School of Computer Science and Artificial Intelligence SR University Warangal Telangana

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Dynamic path planning and collision prevention is one of the key tasks for autonomous vehicles in relation to dynamic movement of obstacles. In this paper, a novel hybrid approach based on integration of Slime Mold Algorithm (SMA), Triangle Inequality Principle (TIP), and Partition Method Strategy (PMS) for solution of this problem statement. The SMA algorithm is very flexible and adaptive by nature due to its biological working mechanism which is associated with TIP and PMS strategies in relation to their optimization and efficient path planning capabilities and robust solutions. This integrated module is tested in virtual environment and the results are compared with other updated algorithms such as A*, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) for the same static and dynamic environment. It has been observed from the results that this hybrid strategy significantly improves the path planning task several times than other algorithms in terms of multiple aspects. Under testing conditions, the path length was reduced to 25% than other algorithms in a dynamic environment. During this calculation, the computational efficiency of the system has been improved to 60% than conventional methods. The chances of collision have been improved to 34.23% especially in environment where the obstacles are moving. The capability of SMA has been improved due to the synergy between TIP and PMS. The dynamic and adaptive nature of this algorithm is suitable for various applications such as search-and-rescue operations, manufacturing units’ automation and other hazardous environment exploration.

关键词： Navigation Heuristic algorithms Virtual environments Path planning Partitioning algorithms Safety Mobile robots Vehicle dynamics Testing Genetic algorithms

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PREFACE: 3^rd international conference on robotics, Intelligent automation and control Technologies (RIACT 2022)

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AIP conference Proceedings 2023年第1期2946卷

作者： Arockia Doss, Arockia Selvakumar Short, Michael Schilberg, Daniel Design and Automation Research Group School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Chennai India School of Computing Engineering and Digital Technologies Teesside University United Kingdom Department of Mechatronics and Mechanical Engineering University of Applied Sciences Bochum Germany

Preface: 3rd international conference on robotics, Intelligent automation and control Technologies (RIACT 2022), AIP conference Proceedings, Volume 2946, Issue

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informatics in control, automation and robotics 2012

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丛书名： Lecture Notes in Electrical Engineering

2012年

作者： Dehuai Yang

ISBN: (数字)9783642259920

ISBN: (纸本)9783642259913

Session 2 includes 110 papers selected from 2011 3rd international Asia conference on informatics in control, automation and robotics (CAR 2011), held on December 24-25, 2011, Shenzhen, China. As we all know, the ever growing technology in robotics and automation will help build a better human society. This session will provide a unique opportunity for the academic and industrial communities to address new challenges, share solutions, and discuss research directions for the future. robotics research emphasizes intelligence and adaptability to cope with unstructured environments. automation research emphasizes efficiency, productivity, quality, and reliability, focusing on systems that operate autonomously. The main focus of this session is on the autonomous acquisition of semantic information in intelligent robots and systems, as well as the use of semantic knowledge to guide further acquisition of information.

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