{"title":"Multi-Robot Coordination Through Mobile Agent","authors":"Binsen Qian, Harry H. Cheng","doi":"10.1109/MESA.2018.8449154","DOIUrl":null,"url":null,"abstract":"Robots can protect humans from risk in many applications, such as search and rescue, outer-space exploration, and toxic cleanup. Multi-robot systems have a huge potential to benefit versatile applications through reconfiguring heterogeneous or homogeneous robots in different ways. This paper presents the design and implementation of RoboCoop, a mobile agent-based framework for automatic coordination of multi-robot systems. RoboCoop consists of several modules, such as knowledge base, Input/Output, task procession/execution, and-sensor reading. The agent-based framework utilizes the innate advantages of themulti-threading of each agent, such that each module can run persistently without blocking others. Modules can exchange information and data through inter-agent communication based on the standards of the Foundation for Intelligent Physical Agents (FIPA). The presented framework allows robots to coordinate, manage, and execute tasks automatically. Also, a backup mechanism is developed to ensure the robustness of robot systems. Moreover, it allows customized algorithms and strategies for task allocation, and execution. A box-pushing mission has been studied to validate the performance of the proposed cooperation framework in several folds, such as task allocation, path planning and motion synchronization. In this validation, boxes need to be assigned to a two-robot team for them to push to a designated position. The A* path planning algorithm is used for robots to drive to the box location. While the robot can push small boxes independently, the big boxes require two robots pushing simultaneously such that the box can move straight to the location.","PeriodicalId":138936,"journal":{"name":"2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MESA.2018.8449154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Robots can protect humans from risk in many applications, such as search and rescue, outer-space exploration, and toxic cleanup. Multi-robot systems have a huge potential to benefit versatile applications through reconfiguring heterogeneous or homogeneous robots in different ways. This paper presents the design and implementation of RoboCoop, a mobile agent-based framework for automatic coordination of multi-robot systems. RoboCoop consists of several modules, such as knowledge base, Input/Output, task procession/execution, and-sensor reading. The agent-based framework utilizes the innate advantages of themulti-threading of each agent, such that each module can run persistently without blocking others. Modules can exchange information and data through inter-agent communication based on the standards of the Foundation for Intelligent Physical Agents (FIPA). The presented framework allows robots to coordinate, manage, and execute tasks automatically. Also, a backup mechanism is developed to ensure the robustness of robot systems. Moreover, it allows customized algorithms and strategies for task allocation, and execution. A box-pushing mission has been studied to validate the performance of the proposed cooperation framework in several folds, such as task allocation, path planning and motion synchronization. In this validation, boxes need to be assigned to a two-robot team for them to push to a designated position. The A* path planning algorithm is used for robots to drive to the box location. While the robot can push small boxes independently, the big boxes require two robots pushing simultaneously such that the box can move straight to the location.