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Design of vision Guidance Transferring System for Automobile Hub Manufacturing 4

Design of Vision Guidance Transferring System for Automobile...

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4th International conference on Electrical, Automation and Mechanical Engineering (EAME)

作者： Zeng, Zhi Zhou, Yongfu Zhong, Guosheng Huizhou Univ Sch Comp Sci & Engn Huizhou Guangdong Peoples R China Heyuan Polytech Inst Elect & Informat Engn Heyuan Guangdong Peoples R China Huizhou Univ Sch Architecture & Civil Engn Huizhou Guangdong Peoples R China

In the era of industrial 4.0 intelligent manufacturing, improving product quality and reducing labor costs are important issues in the transformation and upgrading of manufacturing industry. For Automobile Hub manufacturing, first the whole design of software and hardware based on visual guidance is carried out;then, from the perspective of equipment communication and control, the communication between industrial robot and PC host computer is implemented by using Modbus RTU communication protocol, and PLC control frequency converter is selected to complete the control of transmission unit, and finally, the parameters of camera geometric model are obtained by software identification during the wheel hub to be transferred Now the camera is calibrated, so that the offset can be calculated further to adjust the robot's attitude, and finally the whole process of visual guidance and load transfer can be completed through image recognition. the practice shows that the visual guidance design scheme has been successfully applied to the automatic production line of automobile hub, which improves the production efficiency of the factory and further reduces the cost.

关键词： Industrial robot Automobile Hub Loading vision Guidance

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Target Recognition and Location Based on Deep Learning 4

Target Recognition and Location Based on Deep Learning

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4th IEEE Information Technology, Networking, Electronic and Automation Control conference (ITNEC)

作者： Zhang, Jun Zhou, Zhangli Xing, Luyao Sheng, Xueliang Wang, Meiling Univ Sci & Technol China Sch Informat Sci & Technol Hefei Peoples R China Hefei Inst Phys Sci Inst Adv Mfg Technol Changzhou Peoples R China

ISBN: (纸本)9781728143903

In recent years, more and more people have invested in the research and industrialization of intelligent robots. No matter in the scene of smart home, agriculture, industry or office, the intelligent cognitive level of robot in target recognition and location is far behind that of human. Previous research have relied on computer vision, machine learning and other related technologies. Although a certain effect is achieved, the intelligence level is still low. Using deep learning algorithm and target positioning to explore the real-time and accuracy of target recognition in different environments, and then develop robotic intelligent grasping system, has becoming a research hotspot in the field of computer vision and artificial intelligence. In this paper, based on the improved deep learning algorithm-YOLO, we explored the three-dimensional positioning of the target with a monocular structured light camera. the results show that its performance in real-time, accuracy and other aspects is very significant. It effectively learns the human ability in image recognition and target location, and has the ability of rapid recognition and environmental adaptability.

关键词： deep learning monocular structured light recognition and location computer vision

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Screw Propelled Autonomous Amphibian Waste Collector

Screw Propelled Autonomous Amphibian Waste Collector

引用

International conference on computer and Communications Technologies (ICCCT)

作者： L. Kurinjimalar N. Anitha V. Malini T.N. Hariprasad S.Kalyana Sundaram Sri Sairam Engineering College Chennai India System Engineer Infosys Limited Chennai India SEW Erodrive India Pvt. Ltd Chennai India

ISBN: (纸本)9781665414487

Waste collection has become one of the most challenging tasks in highly populated countries. In places like pond and surrounding's, people gather and put light weight waste regularly. Waste collection in both water and land requires unusual manual effort. However, by using robot with special design it become very easy. In this paper, a novel design of screw propelled amphibian robot is proposed to manage waste collection in both land and water. the robot can work autonomously in wide variety of terrains which includes grass, road, marsh, water, etc. the mechanical design of the robot was developed in computer Aided Design (CAD) and prototype was designed and tested in various working environments. Mobile Application was developed for manual control.

关键词： Design automation Roads robot vision systems Wheels Fasteners Propulsion Sensors

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One Shot Object Detection with Mutual Global Context 21

One Shot Object Detection with Mutual Global Context

引用

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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Object Classification for robotic Platforms 4th

Object Classification for Robotic Platforms

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4th Iberian robotics conference (robot) - Advances in robotics

作者： Brandenburg, Samuel Machado, Pedro Shinde, Pranjali Ferreira, Joao Filipe McGinnity, T. M. Nottingham Trent Univ Computat Neurosci & Cognit Robot Grp Clifton Campus Nottingham NG11 8NS England INESC TEC R Dr Roberto Frias Porto Portugal Univ Coimbra Inst Syst & Robot Polo 2 Coimbra Portugal Ulster Univ Intelligent Syst Res Ctr Magee Campus Magee BT48 7JL Londonderry North Ireland

ISBN: (纸本)9783030361501;9783030361495

computer vision has been revolutionised in recent years by increased research in convolutional neural networks (CNNs);however, many challenges remain to be addressed in order to ensure fast and accurate image processing when applying these techniques to robotics. these challenges consist of handling extreme changes in scale, illumination, noise, and viewing angles of a moving object. the project main contribution is to provide insight on how to properly train a convolutional neural network (CNN), a specific type of DNN, for object tracking in the context of industrial robotics. the proposed solution aims to use a combination of documented approaches to replicate a pick-and-place task with an industrial robot using computer vision feeding a YOLOv3 CNN. Experimental tests, designed to investigate the requirements of training the CNN in this context, were performed using a variety of objects that differed in shape and size in a controlled environment. the general focus was to detect the objects based on their shape;as a result, a suitable and secure grasp could be selected by the robot. the findings in this article reflect the challenges of training the CNN through brute force. It also highlights the different methods of annotating images and the ensuing results obtained after training the neural network.

关键词： Object classification Training YOLOv3 CNN ROS

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Towards a Virtual Coach for Boccia: Developing a Virtual Augmented Interaction based on a Boccia Simulator 15

Towards a Virtual Coach for Boccia: Developing a Virtual Aug...

引用

15th International Joint conference on computer vision, Imaging and computer Graphics theory and Applications (VISIGRAPP) / 4th International conference on Human computer Interaction theory and Applications

作者： Calado, Alexandre Marcutti, Simone Silva, Vinicius Vercelli, Gianni Novais, Paulo Soares, Filomena Univ Minho Algoritmi Ctr Guimaraes Portugal Univ Minho Dept Informat Braga Portugal Univ Genoa Dept Informat Bioengn Robot & Syst Engn Genoa Italy

ISBN: (纸本)9789897584022

Disability can be a factor that leads to social exclusion. Considering that involvement in society is paramount for a person with disability, participation in sports can be a powerful tool for inclusion. Based on this premise, the authors propose an intelligent virtual coach for Boccia to encourage the practice of this sport on persons with disabilities, while promoting social inclusion and shortening the learning curve for individuals new to the sport by learning about game strategy. the envisioned virtual coach will rely on Artificial Intelligence models, thus requiring the creation of large datasets, namely for ball placement and throwing movement recommendations. To answer these problems, this work is focused on the development of a Boccia simulator. With this simulator, it is possible to generate artificial gameplay images and allow the user to control an avatar with body tracking. Gesture recognition was implemented with a state-machine, thus enabling the player to throw the ball, with customizable physics, by performing one of two different throwing movements. this functionality can allow the recording of data describing the body movement associated with the placement of the ball in a certain position within the virtual court, which is essential for the proposed recommendation system.

关键词： Boccia Virtual Reality Gesture Recognition Virtual Coach

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Development and Application of robot Automatic Inspection System Technology Based on Machine Learning

Development and Application of Robot Automatic Inspection Sy...

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IEEE International conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Zhimin Zhang Wen Yang Xinfang Ding Hailin Wan Yiping Yang Methanol Production from Coal Branch of Gansu Huating Coal Electricty Co. LTD Pingliang Gansu China

ISBN: (纸本)9781665428408

With the development of artificial intelligence technology, computer technology and other related technologies, there are more and more researches on mobile robots. the robot has gone through three stages: from a simple teaching and reproducing robot to a low-level intelligent robot with vision, hearing, touch and certain adaptability, and then to a high-level intelligent robot with various advanced sensors and self-adaptive and self-learning functions. Intelligent voice inspection robot can be effectively used in petrochemical, oilfield, nuclear industry and other industries, especially in areas where people are inconvenient to reach, such as pipelines, tanks and towers. the robot is not taught what actions to take, but it evaluates the current state through a value function to select actions to maximize the cumulative reward in the long-term goal. this paper focuses on the design and implementation of intelligent voice inspection robot system, hoping to play a certain reference role for the further improvement and development of intelligent voice inspection robot system in China.

关键词： Industries Service robots Poles and towers Tactile sensors Speech recognition Inspection Security

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Design of vision Servo Sorting robot System Based on SVM 4

Design of Vision Servo Sorting Robot System Based on SVM

引用

2020 4th International Workshop on Advanced Algorithms and Control Engineering, IWAACE 2020

作者： Liu, Yixin Zhong, Shihao Tian, Ziqi He, Kexin Institute of Electrical and Control North China University of Technology Beijing100043 China

Aiming at the problems of the traditional industrial waste disposal, such as heavy workload, low efficiency and poor safety, a single visual servo sorting robot based on SVM is designed. these include intelligent identification and classification systems, and wireless communication systems. the robot adopts a rectangular coordinate robot structure. After collecting picture information, the robot interacts with the upper computer. the SVM algorithm is used to identify and classify the waste material to realize autonomous sorting and transportation of waste material. When the system is applied in practice, it can effectively reduce labor input, improve recovery efficiency, and reduce production costs. © Published under licence by IOP Publishing Ltd.

关键词： Machine design

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TWOLATE: Total Registration of Point-Clouds Using a Weighted Optimal Linear Attitude and Translation Estimator 4

TWOLATE: Total Registration of Point-Clouds Using a Weighted...

引用

4th IEEE conference on Control Technology and Applications (IEEE CCTA)

作者： Qian, Duowen Charland-Arcand, Guillaume Forbes, James Richard ARA Robot Montreal PQ Canada McGill Univ Dept Mech Engn Montreal PQ Canada

ISBN: (纸本)9781728171401

A novel point-cloud registration method that can register points to points, points to planes, and points to lines simultaneously, and in a weighted fashion, is presented. the backbone of the proposed point-cloud registration method is a weighted version of the Optimal Linear Attitude and Translation Estimator (OLATE) called weighted OLATE (WOLATE). the first contribution of this work is the derivation of WOLATE versions of point-to-point, point-to-plane, and point-to-line, all of which take the form of weighted linear least-squares problems. this allows each WOLATE variant to be combined into one large weighted linear least-squares problem. Formulation of this combined registration algorithm, called Total Registration using WOLATE (TWOLATE), is the second contribution of this work. TWOLATE is embedded into a LIDAR odometry pipeline, and is shown to have similar performance relative to state-of-the-art methods, the third contribution of this work.

关键词： computer vision

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4th Iberian robotics conference, robot 2019

4th Iberian Robotics Conference, ROBOT 2019

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4th Iberian robotics conference, robot 2019

ISBN: (纸本)9783030361495

the proceedings contain 57 papers. the special focus in this conference is on Iberian robotics. the topics include: Emergency Landing Spot Detection for Unmanned Aerial Vehicle;ROS Framework for Perception and Dual-Arm Manipulation in Unstructured Environments;modular Dual-Arm robot for Precision Harvesting;integrating Multiple Sources of Knowledge for the Intelligent Detection of Anomalous Sensory Data in a Mobile robot;a Manipulation Control Strategy for Granular Materials Based on a Gaussian Mixture Model;visual and Tactile Fusion for Estimating the Pose of a Grasped Object;object Classification for robotic Platforms;effects of a Social Force Model Reward in robot Navigation Based on Deep Reinforcement Learning;a Cross-Situational Learning Based Framework for Grounding of Synonyms in Human-robot Interactions;robot Navigation to Approach People Using G2-Spline Path Planning and Extended Social Force Model;a Novel Model for Emotion Detection from Facial Muscles Activity;producing Parameterized Value Functions through Modulation for Cognitive Developmental robots;benchmarking Deep and Non-deep Reinforcement Learning Algorithms for Discrete Environments;versatile and Massive Experimentation of robot Swarms in Industrial Scenarios;edge-Enabled Autonomous Navigation and computer vision as a Service: A Study on Mobile robot’s Onboard Energy Consumption and Computing Requirements;a Bio-Inspired Approach for robot Swarm in Smart Factories;Positioning System for UAV Precision Tasks Near Walls in GPS Denied and Metallic Environments;CRAS (Climbing robot for Autonomous InSpection): the Challenges of a High-Temperature Tank;indoor Environment Monitoring in Search of Gas Leakage by Mobile robot;performance of New Global Appearance Description Methods in Localization of Mobile robots;exoFlex: An Upper-Limb Cable-Driven Exosuit.

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