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An Intelligent Anti-theft Cargo Cart with AI Tracking and Camera Pan/Tile Locking Technology

An Intelligent Anti-theft Cargo Cart with AI Tracking and Ca...

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Electronics, Circuits and Information Engineering (ECIE), International conference on

作者： Chang-Hsi Wu Shao-Hsuan Lin Sian-Ci Cheng Rui-Ting Jiang Xiang-Yu Xie Institute of Electronic Engineering Lunghwa UST Taoyuan Taiwan

ISBN: (数字)9798350388312

ISBN: (纸本)9798350388329

this innovative research and development work integrates the mechanism and hardware specification design of Autonomous Mobile robots (AMR), PCB hardware and motor PID control firmware design for four-wheel drive tracking vehicles camera gimbal target recognition and aiming technology, AI vision tracking technology, and anti-theft video recording. It realizes smart vehicle services in large indoor areas such as stores, airports, exhibition halls, or medical institutions, offering personal belongings Cargo, automatic follow and obstacle avoidance, and theft prevention through interaction with a mobile app and the follow cart. through practical tests, we successfully integrated the aforementioned functionalities using the NVIDIA Jetson Xavier NX single-board computer. Achieved a maximum vehicle speed of 1 meters per second, endurance of 1 hour, trajectory tracking error within 75 cm under a refresh rate of 10 Hz, camera gimbal target locking and aiming time within 1 second, and AI vision tracking image processing speed of 8 FPS.

关键词： Target tracking Trajectory tracking Target recognition Prevention and mitigation robot vision systems Cameras Hardware

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A Case Study in Generating 3D Maps with Collaborative robots

A Case Study in Generating 3D Maps with Collaborative Robots

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International conference on

作者： theodor-Radu Grumeza thomas-Andrei Lazăr Isabela Drămnesc Gabor Kusper Konstantinos Papadopoulos Ioannis Lefkos Nikolaos Fachantidis Department of Computer Science West University of Timisoara Timisoara Romania Department of Computer Science Eszterhazy Karoly Catholic University Eger Hungary LIRES Lab University of Macedonia Thessaloniki Greece

ISBN: (数字)9798350391183

ISBN: (纸本)9798350391190

this research presents a case study on the creation of detailed 3D maps using the Agilex Scout Mini robot equipped with a 3D LiDAR, aimed at improving autonomous navigation in indoor environments. ROS (robot Operating System) is employed for real-time data acquisition and processing, and the DBSCAN clustering algorithm for segmenting point cloud data. these maps were subsequently integrated into the humanoid robot Pepper, developed by Aldebaran robotics, enabling Pepper to navigate autonomously and deliver location-based services at the West University of Timisoara. Our results show a point cloud density of approximately 5,000 points per cubic meter, highlighting the LiDAR sensor's capability to capture fine environmental details. Efficient clustering was achieved with an average computation time of 3 seconds per chunk, and path planning demonstrated a high smoothness score of 0.8, improving navigation efficiency. these findings contribute to the field by demonstrating the effectiveness of combining 3D mapping with autonomous robotics for reliable, real-time navigation. Moreover, the integration of Intel RealSense cameras is proposed as a future enhancement to improve object recognition and colour mapping, further expanding the system's potential applications. this case study not only advances academic understanding of autonomous robotic systems but also presents practical and scalable solutions for real-world navigation challenges, offering significant improvements in both accuracy and efficiency.

关键词： Point cloud compression three-dimensional displays Laser radar Navigation robot vision systems Clustering algorithms Real-time systems Path planning Reliability robots

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A Rain Image Generation Approach for Autonomous Driving Perception Sensors

A Rain Image Generation Approach for Autonomous Driving Perc...

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Electronic Information Engineering and computer Science (EIECS), 2021 International conference on

作者： Guozheng Song Shuang Song Sensor and Instrument Center Instrumentation Technology and Economy Institute Beijing China Xiamen University Xiamen China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

Proper rain image generation is important to assess the safety of autonomous perception system in rainy environment and improve perception performance. Rain image generation methods for autonomous driving vision sensors have become a research hotspot. the diversity of data can be extended and the performance of vision-based perception can be improved by effective real rain image generation. Although recent deep learning-based image generation of real rain has good performance, it is still an open problem for autonomous driving scenarios. Firstly, the existing rain images dataset only considers the streak characteristics produced by rain in modeling real rain features, and does not consider the interference of raindrops and fog on the image. Secondly, the distribution of the generated rain streaks, raindrops and fog lacks the influence of physical characteristics brought about by vehicle speed, rainfall and gravity during vehicle operation. Moreover, the lack of a real-time and efficient method for generating realistic raindrop images makes data enhancement and safety testing of sensing systems challenging. To solve the problem of real rain images generation for autonomous driving scenarios, we propose an efficient data generation method that combines physical properties and robot operating system to realize real-time generation of real rain for dynamic scenes and real-time data publish.

关键词： Rain Codecs Image synthesis vision sensors Real-time systems Safety Vehicle dynamics Autonomous vehicles Optical flow Testing

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Active Bionic Visual SLAM and Semantic Map Generation in Building Environments

Active Bionic Visual SLAM and Semantic Map Generation in Bui...

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Electronic Information Engineering and computer Communication (EIECC), International conference on

作者： Yifan Cao Kaifang Wang Wei Song School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

Simultaneous localization and mapping (SLAM) have extensive applications in the field of robotics. However, current visual SLAM mainly constructs semantic maps using passive image information and lacks the ability to autonomously explore the environment. To address this issue, this paper proposes an active semantic capture SLAM system based on a bionic stereo camera, designed for structured environments such as corridors. the system first uses a pose estimation network for initial target localization, then uses the six-degree-of-freedom bionic stereo camera to dynamically adjust the viewpoint, autonomously control the camera to fixate on the target, and optimize the target's pose. Additionally, it analyzes surrounding feature points to determine the position of textual information, guiding the camera to capture it. Experimental results show that, compared to the fixed ORB-SLAM2, the proposed system improves target localization accuracy by an average of 36.1%, effectively integrates object and textual semantic information, and enriches the semantic map.

关键词： Location awareness Visualization Simultaneous localization and mapping Navigation Semantics Buildings robot vision systems Pose estimation Cameras robots

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One Shot Object Detection with Mutual Global Context 21

One Shot Object Detection with Mutual Global Context

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Proceedings of the 2021 4th International conference on Artificial Intelligence and Pattern Recognition

作者： Shihai Jia Tongwei Lu Hao Zhang Hubei Key Laboratory of Intelligent Robot School of Computer ScienceampEngineering Wuhan Institute of Technology China

ISBN: (纸本)9781450384087

At present, DNN-based algorithms have achieved the best performance in some computer vision tasks, but these methods are usually based on large amounts of data. In this work, a new attention mechanism mutual Global Context(mGC) block is proposed for one-shot object detection, which enables RPN head to generate higher-quality region proposals. And abstract this mGC function to get a three-step general framework, which integrates Non-local block and SE block in a brand new way. In order to classify categories that the model has not seen before without training, this paper propose a fully connected classifier for one-shot scenarios. this classifier can classify unseen class without any fine-tuning. this type of classifier provides a new idea for the improvement of metric learning. the experimental results show that the two modules this paper proposed have greatly improved the results of one-shot object detection.

关键词： Attention mechanism Few-shot learning Metric learning One-shot object detection

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Digital Transformation in Mechatronics: ICT Applications in Automation and robotics

Digital Transformation in Mechatronics: ICT Applications in ...

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International conference on ICT in Business Industry & Government (ICTBIG)

作者： Deepshikha Vajpayee Nagesh Gupta Vaishali Joshi School of Computer Science and Information Technology Symbiosis University of Applied Sciences Indore India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

Mechatronics, a multidisciplinary field and transformed the conventional methods to dynamic and autonomous systems. the emergence of robotics and technology in various sectors marks a significant revolution in the industry specially in manufacturing, construction, food, and pharmaceutical industries. this ensured quality, efficiency and precision in the concerned industries. Based on this background, it is from this perspective that the paper addresses transformatory work in collaborative robots, automation technologies, and robotic manipulators through object recognition, human-robot interaction, and machine learning applications. Reviewing the key technologies- machine vision, thermography etc. that transformed the quality control across the industries, enhancing the reliability and precision and efficiency of the *** robots and manipulators in conjunction with the da Vinci Surgical System represent huge promise for surgical purposes and therapeutic interventions within medicine. Discuss some of the challenges in the path planning for system adaptability and insist on the need for robust data in medical robotics, besides the key success factors for adopting robotics in every other sector. this research marks how the growing role of robotics, which includes changing industries that are driving the Fourth Industrial Revolution, offset labor shortages, and growing global demands, is being found.

关键词： Industries Mechatronics Service robots Infrared imaging Quality control robot sensing systems Fourth Industrial Revolution Quality assessment robots Testing

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Hamiltonian-Based Binocular Visual Servoing of Camera-in-Hand robotic Systems

Hamiltonian-Based Binocular Visual Servoing of Camera-in-Han...

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4th International conference on Modelling,Identification and Control(ICMIC 2012)

作者： Bo Yang, Huiguang Li, Zhenbo Kang and Honglei Jiang Institute of Electrical Engineering, University of Yanshan, 066004 Qinhuangdao, China

An image-based strategy visual servo control via Hamiltonian function method for camera-in-hand robotic systems is considered. Firstly, a Hamiltonian realization is proposed for the visual servoing system. We proposed an imagebased visual servo controller for a new binocular stereo vision model which can avoid estimating depth information. Secondly, in accordance with the Hamiltonian realization method the visual servoing system can be modeled as a port-controlled Hamiltonian (PCH) system. For the PCH system, the stability analysis is given. Finally, simulation results are presented to illustrate the performance of the proposed controller.

关键词： hamiltonian visual servoing binocular robot dynamics.

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Research of New Human-computer Interaction Technology based on Visual Recognition

Research of New Human-computer Interaction Technology based ...

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2011 4th IEEE International conference on computer Science and Information Technology(ICCSIT 2011)

作者： Jiaomin Liu,Junying Meng,Yongzheng Li,Juan Wang College of Information Science and Engineering Yanshan University Qinhuangdao,PRC

the desire of looking for a more natural and efficient interactive method that human cantered are increasing *** to this status,this paper try to explore a new human-computer interactive system based on vision recognition,which more natural and more conforms to human behaviour *** new system adopts RBF artificial neural network and Hidden Markov model,locates user's input focus combined with user head and the direction where the finger pointed *** this way,the recognition accuracy and recognition speed of system is *** has wide application prospect in some field such as multimedia teaching,computer game,robot control and home electrical appliance ***,capture human point action by camera and convert it to gray *** identify human face and hand from *** characteristic values which extract from head image to the RBF neural network,gain head's level angle and vertical *** the same time,finger action be divided into three phase and build their Markov model respectively in order to separate the hold-phase and get the direction that finger pointed *** this two parameters,the human-computer interaction focus in camera's coordinate system be determined.

关键词： component visual recognition Hidden Markov Model GRBF face recognition

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Real-Time Video Management for Gas Pipeline Breakage Detection robot Using IoT

Real-Time Video Management for Gas Pipeline Breakage Detecti...

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Innovative Practices in Technology and Management (ICIPTM), International conference on

作者： Ramakrishnan Raman Ashutosh Panchbhai Symbiosis Institute of Business Management Pune & Symbiosis International (Deemed University) Pune Maharashtra India Symbiosis Law School (SLS) Pune & Symbiosis International (Deemed University) Pune Maharashtra India

ISBN: (数字)9798350307757

ISBN: (纸本)9798350307764

this paper proposes an Internet of things (IoT) and a Raspberry Pi-based robot to detect gas pipeline breaks in real-time. A gas sensor, web camera, Wi-Fi connection, cloud server, internet interface, ultrasonic sensors, and motors improve pipeline inspection efficiency and accuracy. the robot checks pipeline gas levels using its gas sensor. the sensor provides real-time data to the Raspberry Pi when it detects an unusual gas concentration. the web camera captures the live video of the pipeline. Using cloud server computer vision, the Raspberry Pi analyses gas sensor data and video feed. the processed footage is sent to a cloud server over Wi-Fi for real-time video monitoring and analysis. the cloud server's internet interface shows the live video stream and warns consumers of pipeline breaks. Advanced video analytics methods identify leaks, breaks, and abnormal flow patterns in the video stream. Ultrasonic sensors on the robot improve detecting accuracy. these sensors assess the distance between the robot and the pipeline for exact localization and positioning during the inspection. the robot's motors allow it to navigate the pipeline for detailed evaluation automatically. the system informs necessary people through the webpage interface in the case of a pipeline breakage. this allows quick reaction and avoidance of gas leaks and pipeline damage concerns. It efficiently detects gas pipeline breaks in real-time. the technology enhances operating efficiency, lowers human inspection hazards, and assures gas infrastructure integrity and safety. this IoT-based technology for real-time surveillance and detection of gas pipeline breakages significantly improves pipeline inspection.

关键词： Cloud computing Accuracy Pipelines Streaming media Inspection Real-time systems Sensors

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Hy-Tech Shopping Cart Using Object Detection and Human Following Technology

Hy-Tech Shopping Cart Using Object Detection and Human Follo...

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International conference on ICT in Business Industry & Government (ICTBIG)

作者： Anita Joshi Tanishq thuse Prashant thorve Raj thakur Anshul thote Isha thakur Department Of Engineering Science and Humanities Vishwakarma Institute Of Technology Pune India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

Recent advancements in artificial intelligence and robotics have transformed the retail industry, leading to innovative solutions that enhance the shopping experience. Our paper presents the High-Tech Shopping Cart, an intelligent system that leverages object detection and human-following technology to provide a seamless, hands-free shopping experience. the cart utilizes state-of-the-art object detection algorithms to identify and track items selected by shoppers while employing a robust human-following mechanism to navigate autonomously through stores. Our system integrates computer vision techniques, sensor fusion, and advanced path-planning algorithms within a modular framework, featuring cameras and depth sensors for real-time processing. Extensive experiments demonstrate high accuracy in object detection and reliable navigation in complex environments. User satisfaction surveys indicate a positive reception, highlighting the cart's potential to significantly enhance the shopping experience.

关键词： Surveys Navigation Service robots Object detection Sensor fusion robot sensing systems Robustness Real-time systems Object recognition Intelligent systems

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