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Local Positioning of an Agricultural Mobile robot Based on a vision System 4th

Local Positioning of an Agricultural Mobile Robot Based on a...

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4th International conference on Agriculture Digitalization and Organic Production, ADOP 2024

作者： Tatur, Mikhail Buren, Maksim Bushuk, Sergey Pashayev, Adalat Sabziev, Elkhan Fu, Minglei Belarusian State University of Informatics and Radioelectronics P. Brovki Street 6 Minsk 220013 Belarus State Scientific and Production Association "Optics Optoelectronics and Laser Technology" Nezavisimosti Avenue 68-1 Minsk220072 Belarus Institute of Control Systems Bakhtiyar Vahabzadeh Street 68 Baku CityAZ1141 Azerbaijan College of Information Engineering Zhejiang University of Technology Liuhe Road 288 Hangzhou310023 China

ISBN: (纸本)9789819744091

Determining coordinates is an important component task for developing a control algorithm for mobile agricultural robots. At the moment, this problem is solved by using global positioning satellite systems. However, satellite connection have not effective forever and everywhere. then, for agricultural land processing, the navigation systems with local positioning could be applied. One of such systems is the visual positioning system based on landmarks. For a long time, its implementation was hampered by the imperfection of systems for recognizing objects in images. However, today neural networks perform computer vision tasks successfully. the purpose of this research was to develop and verify a mathematical model for a positioning system based on optical data of terrain images with beacons. As a result, mathematical formulas were developed to determine the position of the robot in a rectangular coordinate system, and their verification was carried out. the general requirements for the optical system were also worked out and experiments were carried out on real equipment. Ultimately, the performance of the proposed algorithm was proven by conducting an experiment using a real robot with installed camera on it. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Machine vision

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A method for estimating the contribution of an object to scene semantics 4

A method for estimating the contribution of an object to sce...

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4th International conference on computer vision and Information Technology, CVIT 2023

作者： Lin, Zhiyuan Zhu, Feng Wang, Jianyu Wang, Qun Zhao, Pengfei Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Robot Science and Engineering Northeastern University Shenyang110169 China

ISBN: (纸本)9781510672864

the amount of semantic contribution of each object in an image to understand the scene is different. Understanding the relative importance of objects in a scene for scene semantics is critical for various computer vision applications, such as scene recognition and image captioning. In this paper, we refer to the contribution of an object to scene semantics as the degree of its gist and propose a method for Estimating the degree of the Gist of an Instance (EGoI). In the EGoI method, an object gist degree is estimated by the semantic features comparison strategy and the semantic distance comparison strategy. In the first strategy, the image is represented as a scene graph first, then the aggregation features and the node features of different graph node combinations are calculated to estimate the instance gist that is not in the combination of the nodes. In the second strategy, the captions of the complete and incomplete images are generated, then the semantic distance of these captions is used to estimate the instance gist deleted in the scene. Different strategies for estimating the gist degree of instances are tested in the experiments. the results show that the proposed method can effectively quantify the contribution of an instance to scene semantics. Among these strategies, the method that compares semantic features has better discriminative power for the gist degree of various instances in the scene. © 2024 SPIE.

关键词： Semantics

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Real-time mouth shape recognition algorithm based on improved YOLOv7-Tiny 4

Real-time mouth shape recognition algorithm based on improve...

引用

4th International conference on Artificial Intelligence and computer Engineering, ICAICE 2023

作者： Ni, Yongjing Cao, Xue Wang, Jianchao Tang, Xinliang Hebei University of Science and Technology Hebei Shijiazhuang050091 China

ISBN: (纸本)9798400708831

In a complex environment, fast and accurate identification and positioning of the mouth and shape is the key technology of the feeding robot. Aiming at the current scene, a mouth shape recognition method for improving the YOLOv7-Tiny model is proposed. Firstly, the backbone network is partially replaced by MobileNetV3 Small feature extraction, which reduces the size of the model and the amount of parameters;secondly, the spatial pyramid pooling structure is optimized to reduce computing costs;finally, the lightweight multi-scale fusion network Tiny-BiFPN is introduced into the Neck network to solve the loss of features caused by deepening. the test shows that compared with the original model, the accuracy of the improved model has increased by 1.9%, the number of parameters has decreased by 30.59%, and the mAP@0.5value has increased by 0.3%. this research can provide technical support for the later development of feeding robots. © 2023 ACM.

关键词： computer vision

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Research on Mobile robot Localization and Mapping Method for Underground Long-Narrow Tunnels 4

Research on Mobile Robot Localization and Mapping Method for...

引用

4th International conference on robotics and computer vision, ICRCV 2022

作者： Wang, Lei Zhu, Yuqin Liu, Hao Liu, Jia Zhang, Li State Key Laboratory of Coal Mine Safety Technology China Coal Technology Engineering Group Shenyang Research Institute Fushun China Dalian University of Technology School of Mechanical Engineering Dalian China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

the underground roadway scene has few features, which is a typical degraded scene. the commonly used GPS localization methods on the ground can not be directly applied, which brings great challenges to the localization and mapping of mobile robots. this paper proposes to build a laser-UWB fusion slam system to realize the localization and mapping of underground environment to solve the problems. the EKF based method was used to fuse IMU observation information to construct UWB pseudo GNSS localization system. the localization constraints provided by UWB localization system were added to the pose optimization constraints using the graph optimization-based framework and provide a reliable initial estimate for scan matching. then using the original point cloud preprocessing method, i.e., de-distortion, radius filtering, and voxel grid filtering, combines the optimized pose for accurate pose estimation and mapping. Finally, the field experiment shows that the proposed method is closer to the actual trajectory and there is no cumulative error. the odometer error in the X direction has been effectively controlled. Compared with the general slam method, it has a higher ability to resist degradation. © 2022 IEEE.

关键词： Mobile robots

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eyeDog: An assistive-guide robot for the visually impaired

eyeDog: An assistive-guide robot for the visually impaired

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4th ACM International conference on PErvasive Technologies Related to Assistive Environments, PETRA 2011

作者： Galatas, Georgios McMurrough, Christopher Mariottini, Gian Luca Makedon, Fillia Dept. of CSE Heracleia Laboratory University of Texas Arlington TX 76015 United States ASTRA Robotics Lab University of Texas Arlington TX 76015 United States

ISBN: (纸本)9781450307727

Visually impaired people can navigate unfamiliar areas by relying on the assistance of other people, canes, or specially trained guide dogs. Guide dogs provide the impaired person with the highest degree of mobility and independence, but require expensive training and selective breeding. In this paper we describe the design and development of a prototype assistive-guide robot (eyeDog) that provides the visually impaired person with autonomous vision-based navigation and laser-based obstacle avoidance capabilities. this kind of assistive-guide robot has several advantages, such as robust performance and reduced cost and maintenance. the main components of our system are the Create robotic platform (from irobot), a net-book, an on-board USB webcam and a LIDAR unit. the camera is used as the primary exteroceptive sensor for the navigation task;the frames captured by the camera are processed in order to robustly estimate the position of the vanishing point associated to the road/corridor where the eyeDog needs to move. the controller will then steer the robot until the vanishing point and the image center coincide. this condition guarantees the robot to move parallel to the direction of the road/corridor. While moving, the robot uses the LIDAR for obstacle avoidance. © 2011 ACM.

关键词： Hough transforms

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DAFDeTr: Deformable Attention Fusion Based 3D Detection Transformer 1

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4th International conference on robotics, computer vision and Intelligent Systems (ROBOVIS)

作者： Erabati, Gopi Krishna Araujo, Helder Univ Coimbra Inst Syst & Robot P-3030290 Coimbra Portugal

ISBN: (数字)9783031590573

ISBN: (纸本)9783031590566;9783031590573

Existing approaches fuse the LiDAR points and image pixels by hard association relying on highly accurate calibration matrices. We propose Deformable Attention Fusion based 3D Detection Transformer (DAFDeTr) to attentively and adaptively fuse the image features to the LiDAR features with soft association using deformable attention mechanism. Specifically, our detection head consists of two decoders for sequential fusion: LiDAR and image decoder powered by deformable cross-attention to link the multi-modal features to the 3D object predictions leveraging a sparse set of object queries. the refined object queries from the LiDAR decoder attentively fuse with the corresponding and required image features establishing a soft association, thereby making our model robust for any camera malfunction. We conduct extensive experiments and analysis on nuScenes and Waymo datasets. Our DAFDeTr-L achieves 63.4 mAP and outperforms well established networks on the nuScenes dataset and obtains competitive performance on the Waymo dataset. Our fusion model DAFDeTr achieves 64.6 mAP on the nuScenes dataset. We also extend our model to the 3D tracking task and our model outperforms state-of-the-art methods on 3D tracking.

关键词： 3D Object detection Transformer Attention LiDAR Fusion

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PC-Yolo: Enhanced YOLOv5-Based Defect Detection System with Improved Partial Convolution for Ham Sausage Inspection 4

PC-Yolo: Enhanced YOLOv5-Based Defect Detection System with ...

引用

4th International conference on computer vision and Pattern Analysis, ICCPA 2024

作者： Cai, Hexue Shangguan, Haonan Wang, Lulin Faculty of Robot Science and Engineering Northeastern University Liaoning Shenyang110167 China School of Computer Science and Engineering Northeastern University Liaoning Shenyang110167 China School of Metallurgy Northeastern University Liaoning Shenyang110819 China

ISBN: (纸本)9781510682528

Advances in automation for the packaging industry necessitate robust quality control measures, particularly in food appearance inspection. this paper introduces PC-Yolo, an advanced defect detection system based on an enhanced version of the YOLOv5 algorithm, tailored for the inspection of ham sausage products. PC-Yolo incorporates Partial Convolution (PConv) to improve the defect detection process, offering substantial gains in speed and accuracy over traditional methods. A custom dataset comprising high-resolution images of ham sausages, with and without defects, was used to train and validate the model. the proposed system efficiently handles variations in defect size through optimal prior box dimensionality and employs a combination of Feature Pyramid Network (FPN) and Path Aggregation Network (PAN) for effective feature fusion. the resultant PC-Yolo model demonstrates superior real-time detection capabilities, with robust performance in complex scenarios, thereby addressing the industry's zero-defect challenge. © 2024 SPIE.

关键词： Inspection

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An obstacle detection system for a mobile robot based on radar-vision fusion 4th

An obstacle detection system for a mobile robot based on rad...

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4th International conference on computer Engineering and Networks, CENet2014

作者： Chen, Xiao Ren, Weiwu Liu, Mingyang Jin, Lisheng Bai, Yue College of Information and Technology Jilin Agriculture University Changchun130000 China College of Computer Science and Technology Changchun University of Science and Technology Changchun130022 China College of Instrument Science and Electrical Engineering Jilin University Changchun130000 China College of Traffic Jilin University Changchun130000 China Northeast Normal University Changchun130000 China

ISBN: (纸本)9783319111032

this paper presents a systematic scheme for obstacle detection using infrared radar and a monocular vision sensor. On the basis of the visual attention method we use fusion of infrared radar and vision data to obtain better detection performance. In the vision module, salient detection is invalid when no obstacle is present in an image. But infrared radar is used to detect and pre-locate objects. then vision module locate objects by salient location method. Lastly, we test our radarvision system in an indoor simulation environment, and our experiments show that the method is both rapid and feasible. © Springer International Publishing Switzerland 2015.

关键词： Tracking radar

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Dynamic Conveyor Tracking Control of a Delta robot 4th

Dynamic Conveyor Tracking Control of a Delta Robot

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4th Asia Pacific conference on Optics Manufacture, APCOM 2014

作者： Zhang, Guo Ying Liu, Guan Feng Guo, Xiao Bin Lin, Xie Yuan School of Electromechanical Engineering Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9783038356387

For general dynamic pick and place tasks that the objects are transferred with high speed by the conveyor belt, the capability of a delta robot to track the traveling objects is very important for the efficiency. To meet the needs of precision and smooth control, a computed-torque control scheme for conveyor tracking is implemented in this paper. For higher efficiency and accuracy, computer vision system, encoder and conveyor belt region are incorporated into the control scheme. Dividing the conveyor belt into three regions, the robot is commanded to track, pick and give up according to the subregions. Conveyor belt is equipped with an encoder that provides the controller with real-time position and speed of the belt. Based upon those informations, the controller automatically compensates the end positions with respect to the belt to adjust for the position of the conveyor. then, the conveyor tracking problem is converted to a subregional tracking problem. © 2016 Trans Tech Publications Ltd, Switzerland.

关键词： Torque control

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Biomimetic and Biohybrid Systems 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Stuart P. Wilson Tony J. Prescott Paul F.M.J. Verschure Anna Mura

ISBN: (数字)9783319229799

ISBN: (纸本)9783319229782

this book constitutes the proceedings of the 4th International conference on Biomimetic and Biohybrid Systems, Living Machines 2015, held in Barcelona, Spain, in July 2015. the 34 full and 13 short papers presented in this volume were carefully reviewed and selected from 50 submissions. the themes they deal with are: locomotion, particularly for soft-bodies; novel sensing and autonomous control systems; and cognitive architectures, social robots, and human-robot interaction.

关键词： Artificial Intelligence computer Imaging, vision, Pattern Recognition and Graphics theory of Computation Data Mining and Knowledge Discovery

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