Improving constrained glider trajectories for ocean eddy border sampling within extended mission planning time

Zamuda, Aleš; Sosa, José Daniel Hernández; Adler, Leonhard

doi:10.1109/cec.2016.7743997

Cited by 6 publications

(1 citation statement)

References 34 publications

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“…During the execution of a plan by an AUV, unexpected events might occur that provide opportunities for the vehicle to increase the overall utility of its operations [28]. An example is that a part-submerged section of an anchor chain, or other structure, might be spotted during the execution of a mission [2], [29].…”

Section: Opportunistic Planningmentioning

confidence: 99%

Opportunistic Planning in Autonomous Underwater Missions

Cashmore

Fox

Long

et al. 2018

IEEE Trans. Automat. Sci. Eng.

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Abstract-This paper explores the execution of planned AUV missions where opportunities to achieve additional utility can arise during execution. The missions are represented as temporal planning problems, with hard goals and time constraints. Opportunities are soft goals with high utility. The probability distributions for the occurrences of these opportunities are not known, but it is known that they are unlikely so it is not worth trying to anticipate their occurrence prior to plan execution. However, as they are high utility, it is worth trying to address them dynamically when they are encountered, as long as this can be done without sacrificing the achievement of the hard goals of the problem. We formally characterise the opportunistic planning problem, introduce a novel approach to opportunistic planning and compare it to an on-board replanning approach in the domain of autonomous underwater vehicles performing pillar expection and chain following tasks.Note to Practitioners-This paper concerns high level intelligent automation of unmanned vehicle operations in the context of undersea inspection and maintenance. The objective is to provide a robust long-term autonomy, enabling the vehicle to make its own decisions about how to prioritise goals and use its resources. Plans to achieve large numbers of goals over time are constructed autonomously by a planning system using models of activity and resource consumption. In order to avoid running up against resource bounds in a way that would compromise robustness, models of resource consumption are conservative. An important aspect of long-term autonomy concerns how unused resources, that accumulate over time because of conservative assumptions, can be used to increase overall utility. The approach we describe is deterministic: we do not model uncertainty or allow the planner to reason with contingencies. Instead, we focus on how to exploit resource intelligently to obtain the best available utility, in a way that does not undermine the reliability or predictability of operational behaviour.

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Section: Opportunistic Planningmentioning

confidence: 99%