Showing papers on "Intervention AUV published in 2018"

Autonomous Underwater Intervention: Experimental Results of the MARIS Project

Abstract: Autonomous underwater vehicles are frequently used for survey missions and monitoring tasks, however, manipulation and intervention tasks are still largely performed with a human in the loop. Employing autonomous vehicles for these tasks has received a growing interest in the last ten years, and few pioneering projects have been funded on this topic. Among these projects, the Italian MARIS project had the goal of developing technologies and methodologies for the use of autonomous underwater vehicle manipulator systems in underwater manipulation and transportation tasks. This work presents the developed control framework, the mechatronic integration, and the project's final experimental results on floating underwater intervention.

Opportunistic Planning in Autonomous Underwater Missions

Abstract: This paper explores the execution of planned autonomous underwater vehicle (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 characterize the opportunistic planning problem, introduce a novel approach to opportunistic planning, and compare it with an on-board replanning approach in the domain of AUVs 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 prioritize 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 behavior.