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Title:Survey on autonomous surface vessels: Part I - A new detailed definition of autonomy levels
Authors:M. Schiaretti, L. Chen, R.R. Negenborn

Conference:8th International Conference on Computational Logistics (ICCL 2017)
Address:Southampton, UK
Date:October 2017

Abstract:Autonomous Surface Vessels (ASVs) have been involved in numerous projects since 1990. Many ASV projects have been successfully realized, and as many are still under development. Together with the development of those new autonomous vessels, the research on classification about ASVs become a hot point. The classifications provides clarity to researchers, designers, shipbuilders, equipment manufacturers, ship owners and operators, enabling accurate specification of the desired level of autonomy in design and operations. Moreover, the relative research paves the way to a clearer understanding of the opportunity and challenges of research on autonomous vehicles. In this paper, we introduced the emerging concept of autonomous vessels. A multi-layer multi-agent control architecture of cooperative transport system from the perspective of ASVs were proposed. Moreover, we made an overview of existing research on the classification of autonomy. Based on the analysis, detailed definition and categorization of autonomy levels for ASVs are proposed based on the characteristics of ASVs and existing classification of autonomy. The proposed autonomy levels categorization points out the the main aspects in ASV research. It assesses the overall autonomy level of a vessel by analyzing the automated sub-systems: Decision, Actions, Exceptions, and Cooperation. This categorization can be used to analyze existing ASV prototypes to gain insight into the status and tend of ASV research (present in our another paper).

Reference:M. Schiaretti, L. Chen, R.R. Negenborn. Survey on autonomous surface vessels: Part I - A new detailed definition of autonomy levels. Accepted for the 8th International Conference on Computational Logistics (ICCL 2017), Southampton, UK, October 2017.
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