Informed Sampling-based Collision Avoidance with Least Deviation from the Nominal Path

Thomas Thuesen Enevoldsen, Roberto Galeazzi

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Abstract

This paper addresses local path re-planning for n-dimensional systems by introducing an informed sampling scheme and cost function to achieve collision avoidance with minimum deviation from an (optimal) nominal path. The proposed informed subset consists of the union of ellipsoids along the specified nominal path, such that the subset efficiently encapsulates all points along the nominal path. The cost function penalizes large deviations from the nominal path, thereby ensuring current safety in the face of potential collisions while retaining most of the overall efficiency of the nominal path. The proposed method is demonstrated on scenarios related to the navigation of autonomous marine crafts.
Original languageEnglish
Title of host publicationProceedings of 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE
Publication date2023
Pages8094-8100
ISBN (Print)978-1-6654-7928-8
DOIs
Publication statusPublished - 2023
Event2022 IEEE/RSJ International Conference on Intelligent Robots and Systems - Kyoto International Conference Center, Kyoto, Japan
Duration: 23 Oct 202227 Oct 2022
https://iros2022.org/

Conference

Conference2022 IEEE/RSJ International Conference on Intelligent Robots and Systems
LocationKyoto International Conference Center
Country/TerritoryJapan
CityKyoto
Period23/10/202227/10/2022
Internet address

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