Multi-USV Collaborative Obstacle Avoidance Based on Improved Velocity Obstacle Method-Reference-Cited by-同舟云学术

Multi-USV Collaborative Obstacle Avoidance Based on Improved Velocity Obstacle Method

Published:2024-03 Issue:1 Volume:10 Page:
ISSN:2376-7642
Container-title:ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
language:en
Short-container-title:ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng.

Author:

Du Zhe¹,Li Weifeng²,Shi Guoyou³

Affiliation:

1. Ph.D. Student, Navigation College, Dalian Maritime Univ., Dalian 116026, PR China.

2. Professor, Navigation College, Dalian Maritime Univ., Dalian 116026, PR China (corresponding author).

3. Professor, Navigation College, Dalian Maritime Univ., Dalian 116026, PR China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/AJRUA6.RUENG-1174

Reference28 articles.

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4. Garcia A. S. S. Mittal E. Kiewra and K. Ghose. 2019. “A convolutional neural network feature detection approach to autonomous quadrotor indoor navigation.” In Proc. Paper Presented at the 2019 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS). New York: IEEE.

5. Generalized velocity obstacle algorithm for preventing ship collisions at sea

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