TML:a language to specify aerial robotic missions for the framework Aerostack
作者机构：Department of Artificial IntelligenceTechnical University of Madrid(UPM)MadridSpain Centre for Automation and RoboticsTechnical University of MadridMadridSpain
出 版 物：《International Journal of Intelligent Computing and Cybernetics》 (智能计算与控制论国际期刊（英文）)
年 卷 期：2017年第10卷第4期
页 面：491-512页
核心收录：
学科分类：0502[文学-外国语言文学] 0810[工学-信息与通信工程] 050201[文学-英语语言文学] 05[文学] 0808[工学-电气工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：This research work has been partially supported by the Spanish Ministry of Economy and Competitiveness through the project VA4UAV(Visual autonomy for UAV in Dynamic Environments),reference DPI2014-60139-R The authors would like to thank the members of our research group CVAR(Computer Vision and Aerial Robotics)for their help in software programming and evaluation with real flights:David Palacios,Adrian Diaz-Moreno,Guillermo de Fermin,Alberto Camporredondo and Carlos Valencia.
主 题：Adaptive mission plans Aerial robotic systems Autonomous aerial systems Mission plan specification
摘 要：Purpose–The purpose of this paper is to describe the specification language TML for adaptive mission plans that the authors designed and implemented for the open-source framework Aerostack for aerial robotics.Design/methodology/approach–The TML language combines a task-based hierarchical approach together with a more flexible representation,rule-based reactive planning,to facilitate adaptability.This approach includes additional notions that abstract programming details.The authors built an interpreter integrated in the software framework Aerostack.The interpreter was validated with flight experiments for multi-robot missions in dynamic environments.Findings–The experiments proved that the TML language is easy to use and expressive enough to formulate adaptive missions in dynamic environments.The experiments also showed that the TML interpreter is efficient to execute multi-robot aerial missions and reusable for different platforms.The TML interpreter is able to verify the mission plan before its execution,which increases robustness and safety,avoiding the execution of certain plans that are not feasible.Originality/value–One of the main contributions of this work is the availability of a reliable solution to specify aerial mission plans,integrated in an active open-source project with periodic releases.To the best knowledge of the authors,there are not solutions similar to this in other active open-source projects.As additional contributions,TML uses an original combination of representations for adaptive mission plans(i.***.task trees with original abstract notions and rule-based reactive planning)together with the demonstration of its adequacy for aerial robotics.
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