J. Robotics最新文献_第10页

Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things 物联网环境下基于改进蚁群算法的机器人路径规划

J. Robotics Pub Date : 2022-04-04 DOI: 10.1155/2022/1739884

Hong-Kai Huang, Guo Tan, Linli Jiang

{"title":"Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things","authors":"Hong-Kai Huang, Guo Tan, Linli Jiang","doi":"10.1155/2022/1739884","DOIUrl":"https://doi.org/10.1155/2022/1739884","url":null,"abstract":"It is a research topic of practical significance to study the path planning technology of mobile robot navigation technology. Aiming at the problems of slow convergence speed, redundant planning path, and easy to fall into local optimal value of ant colony algorithm in a complex environment, a robot path planning based on improved ant colony algorithm is proposed. First, the grid method is used to model the path environment, which marks each grid to make the ant colony move from the initial grid to the target grid for path search. Second, the ant colony is divided according to different planning tasks. Let some ants explore the way first, and carry out basic optimization planning for the map environment. The antecedent ants mark the basic advantage on a target value of the path with pheromone concentration so as to guide the subsequent route-finding operation of the main ant colony. Finally, in order to avoid the individual ants falling into a deadlock state in the early search, the obstacle avoidance factor is increased, the transition probability is improved, and the amount of information on each path is dynamically adjusted according to the local path information, so as to avoid the excessive concentration of pheromones. Experimental results show that the algorithm has high global search ability, significantly speeds up the convergence speed, and can effectively improve the efficiency of mobile robot in path planning.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125310745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Waypoint Tracking Control for Autonomous Mobile Sampling and Dissolved Oxygen Enrichment of Unmanned Surface Vehicle 无人水面车辆自主移动采样与溶解氧富集航路点跟踪控制

J. Robotics Pub Date : 2022-03-31 DOI: 10.1155/2022/3652329

Jian Yuan, Hailin Liu, Wenxia Zhang

{"title":"Waypoint Tracking Control for Autonomous Mobile Sampling and Dissolved Oxygen Enrichment of Unmanned Surface Vehicle","authors":"Jian Yuan, Hailin Liu, Wenxia Zhang","doi":"10.1155/2022/3652329","DOIUrl":"https://doi.org/10.1155/2022/3652329","url":null,"abstract":"An autonomous monitoring and control system of unmanned surface vehicle (USV) with mobile water quality monitoring, sampling, and oxygenation functions is constructed. The control hardware and monitoring configuration software of the system is designed, respectively, which can be installed on USV and its remote control and monitoring terminal. The kinematic modeling of USV, waypoint trajectory-tracking control, distributed controller, simulation of tracking control, and verification of software and hardware design are carried out. In order to reject the system noise and external noise, a states estimation method with fully observable states is considered in the control law design. The software and hardware are also implemented to verify the effectiveness of the monitoring platform. Through setting a series of monitoring target points and monitoring parameters in the configuration software of the remote user terminal or in the APP of the mobile user terminal, the USV can realize the automatic cruise monitoring using an autonomous navigation and tracking control algorithm, and quantitative water sampling collection. The reliability of the system is verified by the experiment of the shore test station, and the waypoint trajectory tracking and sensors data are replaying in a logview GUI of MOOS-Ivp and APP.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"146 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129784186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment 物联网环境下5G通信无人机辅助边缘计算资源分配策略

J. Robotics Pub Date : 2022-03-31 DOI: 10.1155/2022/9397783

Hao Liu

引用次数: 1

Intelligent Obstacle Avoidance Algorithm for Mobile Robots in Uncertain Environment 不确定环境下移动机器人的智能避障算法

J. Robotics Pub Date : 2022-03-30 DOI: 10.1155/2022/8954060

Liwei Guan, Yu Lu, Zhijie He, Xi Chen

{"title":"Intelligent Obstacle Avoidance Algorithm for Mobile Robots in Uncertain Environment","authors":"Liwei Guan, Yu Lu, Zhijie He, Xi Chen","doi":"10.1155/2022/8954060","DOIUrl":"https://doi.org/10.1155/2022/8954060","url":null,"abstract":"The application of mobile robots and artificial intelligence technology has shown great application prospects in many fields. The ability of intelligent obstacle avoidance is the basis for the deep application of mobile robots. However, there are often more or less uncertain factors in the actual operating environment of the robot, such as people or objects that are not updated in time or temporarily appear. Therefore, it is an important step to complete the automatic learning of obstacle avoidance for mobile robots. In a nondeterministic environment, a mobile robot intelligent obstacle avoidance algorithm based on an improved fuzzy neural network with self-learning is firstly proposed. The mobile robot intelligent obstacle avoidance system is constructed through the reaction layer, the deliberation layer, and the supervision layer. Through the analysis of sensor performance, model accuracy, path obstacle avoidance optimization, and obstacle avoidance simulation, the following conclusions are drawn. First, through network training, the accuracy rate of the test set is stable at 98%, and the loss of the function value has also been reduced from the original 0.79 to 0.08, which is 10 times smaller. Second, the traditional single sensor cannot meet the obstacle avoidance requirements of robots, and mobile robots must combine multipurpose technology. Third, the algorithm in this paper encounters the following. When there are obstacles, the path is dominated by straight lines, obstacle avoidance planning is optimal, and the distance is shorter. Fourth, the larger N : M, the larger the solution space, indicating that this algorithm gradually improves the search efficiency to the greatest extent and can handle any form of medium and large scale task allocation problem.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123775056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Network Resource Allocation Strategy Based on UAV Cooperative Edge Computing 基于无人机合作边缘计算的网络资源分配策略

J. Robotics Pub Date : 2022-03-29 DOI: 10.1155/2022/8514235

ShuoHao Wang, Ning Kong

引用次数: 2

Recognition and Localization of Target Images for Robot Vision Navigation Control 机器人视觉导航控制中目标图像的识别与定位

J. Robotics Pub Date : 2022-03-24 DOI: 10.1155/2022/8565913

Muji Chen

{"title":"Recognition and Localization of Target Images for Robot Vision Navigation Control","authors":"Muji Chen","doi":"10.1155/2022/8565913","DOIUrl":"https://doi.org/10.1155/2022/8565913","url":null,"abstract":"This paper focuses on a visual navigation control system for mobile robots, recognizing target images and intelligent algorithms for the navigation system’s path tracking and localization techniques. This paper examines the recognition and localization of target images based on the visual navigation control of mobile robots. It proposes an efficient marking line method for recognizing and localization target images. Meanwhile, a fuzzy control method with smooth filtering and high efficiency is designed to improve the stability of robot operation, and the feasibility is verified in different scenarios. The corresponding image acquisition system is developed according to the characteristics of the experimental environment, and the acquired images are preprocessed to obtain corrected grayscale images. Then, target image recognition and linear fitting are performed to obtain target image positioning. The system calculates the angle and distance of the mobile robot, offsetting the target image in real time, adjusting the output signal, and controlling the mobile robot to realize path tracking. The comparison of sensor data and path tracking algorithm results during the experiment shows that the path tracking algorithm achieves good results with an angular deviation of ±1.5°. The application of RANSAC algorithm and improved Hough algorithm was analyzed in visual navigation control, and the two navigation line detection algorithms based on the image characteristics of the target image were improved in the optical detection area of the navigation line for the shortcomings of the two algorithms in visual navigation control, and the algorithms before and after the improvement were compared.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132742561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unmanned Aerial Vehicle Surveying and Mapping Trajectory Scheduling and Autonomous Control for Landslide Monitoring 滑坡监测无人机测绘轨迹调度与自主控制

J. Robotics Pub Date : 2022-03-24 DOI: 10.1155/2022/2365006

Shifang Liao, Manzhu Ye, Rongcai Yuan, Wanzhi Ma

{"title":"Unmanned Aerial Vehicle Surveying and Mapping Trajectory Scheduling and Autonomous Control for Landslide Monitoring","authors":"Shifang Liao, Manzhu Ye, Rongcai Yuan, Wanzhi Ma","doi":"10.1155/2022/2365006","DOIUrl":"https://doi.org/10.1155/2022/2365006","url":null,"abstract":"Real-time and efficient monitoring of geological disasters has received extensive attention in the application of UAV surveying and mapping control technology. The application of traditional landslide monitoring methods lacks the accuracy of control algorithms, which has become a hot issue currently facing. Based on the landslide surface subsidence monitoring method, this article designs the UAV trajectory scheduling subsidence monitoring software, which can monitor the UAV’s flight status and navigation information, and draw the flight trajectory in real time. At the same time, the model solves the problem of storage and management of landslide inspection results by the landslide inspection management system, and realizes the functions of entering and querying landslide information, viewing inspection results, landslide safety judgment, generating reports, and autonomous control. The simulation results show that the global accuracy reaches 0.975, and the algorithm recognition degree reaches 99.8%, which promotes the reliability of the landslide monitoring data for the identification of the surveying and mapping trajectory, and provides a decision-making basis for landslide treatment.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115197325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Personalized Product Recommendation Model of Automatic Question Answering Robot Based on Deep Learning 基于深度学习的自动问答机器人个性化产品推荐模型

J. Robotics Pub Date : 2022-03-22 DOI: 10.1155/2022/1256083

Jie Peng, Jianhui Xu

{"title":"Personalized Product Recommendation Model of Automatic Question Answering Robot Based on Deep Learning","authors":"Jie Peng, Jianhui Xu","doi":"10.1155/2022/1256083","DOIUrl":"https://doi.org/10.1155/2022/1256083","url":null,"abstract":"The collaborative filtering algorithm widely used in recommendation systems has problems with the sparsity of scoring data and the cold start of new products. A personalized product recommendation model for automated question-answering robots using deep learning is proposed. First, a personalized attention mechanism at the word level and the comment level is proposed, and the comments and users are individually coded. Then, the bidirectional gated recurrent unit (Bi-GRU) is used to construct the score prediction matrix, and through the dynamic collaborative filtering algorithm to integrate the time characteristics of the user’s interest changes. Finally, the feature codes of the users and products are input into the Bi-GRU model for learning, so as to output the recommendation list of personalized products of the automated question answering robot. Experimental results based on the JD and Tianchi datasets show that the training loss of the proposed model is lower than 45 and 23, respectively. And HR@15 and MRR@15 exceed 48 and 15, respectively, which are better than other comparison models. It can better adapt to the actual needs of automatic question-answering robots.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115139181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Research and Implementation of Turbo Coding Technology in High-Speed Underwater Acoustic OFDM Communication 高速水声OFDM通信中Turbo编码技术的研究与实现

J. Robotics Pub Date : 2022-03-15 DOI: 10.1155/2022/2576303

Yarang Yang, Yunpeng Li

{"title":"Research and Implementation of Turbo Coding Technology in High-Speed Underwater Acoustic OFDM Communication","authors":"Yarang Yang, Yunpeng Li","doi":"10.1155/2022/2576303","DOIUrl":"https://doi.org/10.1155/2022/2576303","url":null,"abstract":"It is demonstrated that the fully parallel turbo decoding algorithm can achieve an approximate error correction decoding performance when 36 iterations are used and when the log-map algorithm with 6 iterations is used. By comparison, it is shown that it can achieve much higher decoding rates than the log-map algorithm for various frame lengths of LTE standard turbo codes at the cost of higher hardware resource requirements. According to the fully parallel turbo decoding algorithm, this paper proposes a scheme for implementing a fully parallel turbo decoder on FPGA, detailing the overall structure and processing of the decoder hardware implementation, the design of the algorithm block processing unit, and the interleaving module. The performance of the decoder is tested by fixed-point simulation for different frame lengths of turbo coding in LTE standard, and it is proved that the fully parallel turbo decoder can be applied to turbo coding of various frame lengths. Both simulation and experimental results show that the distributed cancellation method and the joint estimation cancellation method have good results for both time-domain impulse noise and large-amplitude single frequency noise cancellation, while the joint estimation cancellation method of large-amplitude single frequency noise cancellation first has better performance.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114425510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Improved VM Obstacle Identification Method for Reflection Road 一种改进的反射道路虚拟机障碍物识别方法

J. Robotics Pub Date : 2022-03-14 DOI: 10.1155/2022/3641930

Guoxin Jiang, Yi Xu, Xiaoqing Sang, Xiao-Jin Gong, Shanshan Gao, Ruoyu Zhu, Liming Wang, Yuqiong Wang

引用次数: 1