TML: a language to specify aerial robotic missions for the framework Aerostack. Issue 4 (13th November 2017)

• Record Type: Journal Article
• Authors: Molina, Martin; Suarez-Fernandez, Ramon A.; Sampedro, Carlos; Sanchez-Lopez, Jose Luis; Campoy, Pascual
• Is Part Of: International journal of intelligent computing and cybernetics. Volume 10:Issue 4(2017)
• Page Start: 491
• Page End: 512
• Publication Date: 2017-11-13
• Subjects: Adaptive mission plans -- Aerial robotic systems -- Autonomous aerial systems -- Mission plan specification; Artificial intelligence -- Periodicals; Cybernetics -- Periodicals; 006.3
• DOI: 10.1108/IJICC-03-2017-0025
• Languages: English
• ISSNs: 1756-378X

Abstract

Abstract : 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.e. task trees with original abstract notions and rule-based reactive planning) together with the demonstration of its adequacy for aerial robotics.