{"title":"利用协同无人地面车辆覆盖农田","authors":"S. Faryadi, Mohammadreza Davoodi, J. M. Velni","doi":"10.1115/dscc2019-8992","DOIUrl":null,"url":null,"abstract":"\n In this paper, a distributed algorithm with obstacle avoidance capability is presented to deploy a group of ground robots for field-based agriculture applications. To this end, the field (consisting of many plots) is first modeled as a directed graph, and the robots are deployed to collect data from some important areas of the field (e.g., areas with high water stress or biotic stress). The key idea is to formulate the underlying problem as a locational optimization problem and then find the optimal solution based on the Voronoi partitioning of the associated graph. The proposed partitioning method is validated through simulation studies, as well as experiments using a group of mobile robots.","PeriodicalId":41412,"journal":{"name":"Mechatronic Systems and Control","volume":"269 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2019-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Agricultural Field Coverage Using Cooperating Unmanned Ground Vehicles\",\"authors\":\"S. Faryadi, Mohammadreza Davoodi, J. M. Velni\",\"doi\":\"10.1115/dscc2019-8992\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n In this paper, a distributed algorithm with obstacle avoidance capability is presented to deploy a group of ground robots for field-based agriculture applications. To this end, the field (consisting of many plots) is first modeled as a directed graph, and the robots are deployed to collect data from some important areas of the field (e.g., areas with high water stress or biotic stress). The key idea is to formulate the underlying problem as a locational optimization problem and then find the optimal solution based on the Voronoi partitioning of the associated graph. The proposed partitioning method is validated through simulation studies, as well as experiments using a group of mobile robots.\",\"PeriodicalId\":41412,\"journal\":{\"name\":\"Mechatronic Systems and Control\",\"volume\":\"269 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2019-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mechatronic Systems and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/dscc2019-8992\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mechatronic Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/dscc2019-8992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Agricultural Field Coverage Using Cooperating Unmanned Ground Vehicles
In this paper, a distributed algorithm with obstacle avoidance capability is presented to deploy a group of ground robots for field-based agriculture applications. To this end, the field (consisting of many plots) is first modeled as a directed graph, and the robots are deployed to collect data from some important areas of the field (e.g., areas with high water stress or biotic stress). The key idea is to formulate the underlying problem as a locational optimization problem and then find the optimal solution based on the Voronoi partitioning of the associated graph. The proposed partitioning method is validated through simulation studies, as well as experiments using a group of mobile robots.
期刊介绍:
This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.