Cassandra McCord, J. P. Queralta, Tuan Anh Nguyen Gia, Tomi Westerlund
{"title":"Distributed Progressive Formation Control for Multi-Agent Systems: 2D and 3D deployment of UAVs in ROS/Gazebo with RotorS","authors":"Cassandra McCord, J. P. Queralta, Tuan Anh Nguyen Gia, Tomi Westerlund","doi":"10.1109/ECMR.2019.8870934","DOIUrl":null,"url":null,"abstract":"Coordination of multiple robots in order to cooperatively perform a given task requires a certain distribution of the different units in space. Furthermore, individual robots, or agents, might have different tasks, or positions, assigned. Formation control algorithms might rely on a priori information, a centralized controller, or communication among the agents to assign roles. Distributed approaches that only need local interaction between agents have limited possibilities, such as flocks where agents actively control the distance to neighboring agents. Alternatively, two-way local communication has been applied to progressively assign roles and converge towards a given configuration. We propose a progressive assignment algorithm and formation control scheme that extends leader-follower formations in order to enable cooperation of multiple robots with minimal, one-way, local communication between agents. The proposed algorithm progressively generates a directed, locally convex, path graph to uniquely assign formation positions to all agents. The low computational complexity of our algorithm enables its implementation in resource-limited devices. Agents only require information about neighboring agents and be able to locally broadcast their status. This algorithm enables almost arbitrary two-dimensional configurations, with the only limitation being the sensing range enabling the definition of a series of convex hulls in a certain subset of agents such that agents sharing an edge in the hull are able to sense each other. Moreover, we propose a methodology for deploying agents to an arbitrary three-dimensional configuration after the assignment process is made on the plane.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 European Conference on Mobile Robots (ECMR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECMR.2019.8870934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
Coordination of multiple robots in order to cooperatively perform a given task requires a certain distribution of the different units in space. Furthermore, individual robots, or agents, might have different tasks, or positions, assigned. Formation control algorithms might rely on a priori information, a centralized controller, or communication among the agents to assign roles. Distributed approaches that only need local interaction between agents have limited possibilities, such as flocks where agents actively control the distance to neighboring agents. Alternatively, two-way local communication has been applied to progressively assign roles and converge towards a given configuration. We propose a progressive assignment algorithm and formation control scheme that extends leader-follower formations in order to enable cooperation of multiple robots with minimal, one-way, local communication between agents. The proposed algorithm progressively generates a directed, locally convex, path graph to uniquely assign formation positions to all agents. The low computational complexity of our algorithm enables its implementation in resource-limited devices. Agents only require information about neighboring agents and be able to locally broadcast their status. This algorithm enables almost arbitrary two-dimensional configurations, with the only limitation being the sensing range enabling the definition of a series of convex hulls in a certain subset of agents such that agents sharing an edge in the hull are able to sense each other. Moreover, we propose a methodology for deploying agents to an arbitrary three-dimensional configuration after the assignment process is made on the plane.