An Adaptive Velocity Obstacle Avoidance Algorithm for Autonomous Surface Vehicles

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Daniel Filipe Campos (Author) Other; Aníbal Castilho Coimbra de Matos (Author) FEUP; Andry Maykol Pinto (Author) FEUP

Conference proceedings International

Title: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019, Macau, SAR, China, November 3-8, 2019

Pages: 8089-8096

Indexing

ISI Web of Knowledge - 9 Citations

Scopus - 4 Citations

Other information

Authenticus ID: P-00R-VZ8

DOI: 10.1109/iros40897.2019.8968156

Abstract (EN): This paper presents a new algorithm for a real-time obstacle avoidance for autonomous surface vehicles (ASV) that is capable of undertaking preemptive actions in complex and challenging scenarios. The algorithm is called adaptive velocity obstacle avoidance (AVOA) and takes into consideration the kinematic and dynamic constraints of autonomous vessels along with a protective zone concept to determine the safe crossing distance to obstacles. A configuration space that includes both the position and velocity of static or dynamic elements within the field-of-view of the ASV is supporting a particle swarm optimization procedure that minimizes the risk of harm and the deviation towards a predefined course while generating a navigation path with capabilities to prevent potential collisions. Extensive experiments demonstrate the ability of AVOA to select a velocity estimative for ASVs that originates a smoother, safer and, at least, two times more effective collision-free path when compared to existing techniques.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8