Intelligent Obstacle Avoidance and Path Planning for Unmanned Vessels Based on an Improved Bug2 Algorithm

With the rapid development of artificial intelligence technology, the demand for intelligence in unmanned vessels is becoming increasingly prominent. One of the core problems in the process of automatic navigation of unmanned vessels is how to make effective collision avoidance decisions in time. In this paper, an improved Bug2 algorithm is proposed, which introduces angle determination and bypassing strategy in the traditional Bug2 algorithm, effectively solves the deficiencies of the conventional Bug2 algorithm in the fixed obstacle avoidance direction and timing of the movement, and significantly improves the dynamic obstacle avoidance performance of the algorithm. The dynamic obstacle simulation test verifies that the algorithm has high real-time and strong path planning ability. After that, the unmanned boat control system is designed, and in the physical test on the lake, the unmanned boat can rely on the improved Bug2 algorithm to plan the obstacle avoidance path in time when encountering obstacles, realizing the autonomous obstacle avoidance, which provides solid technical support for intelligent navigation in the complex sea area.

Authors

Institutions

Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/ricai64321.2024.10911122
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligent Obstacle Avoidance and Path Planning for Unmanned Vessels Based on an Improved Bug2 Algorithm

Xu Mao, Bo Wang, Zhi‐Kuan Chen, Yi Lou et al.
Robotic Path Planning Algorithms
article

Intelligent Obstacle Avoidance and Path Planning for Unmanned Vessels Based on an Improved Bug2 Algorithm

Xu Mao, Bo Wang, Zhi‐Kuan Chen, Yi Lou, Zhiquan Zhou
article en

Abstract

With the rapid development of artificial intelligence technology, the demand for intelligence in unmanned vessels is becoming increasingly prominent. One of the core problems in the process of automatic navigation of unmanned vessels is how to make effective collision avoidance decisions in time. In this paper, an improved Bug2 algorithm is proposed, which introduces angle determination and bypassing strategy in the traditional Bug2 algorithm, effectively solves the deficiencies of the conventional Bug2 algorithm in the fixed obstacle avoidance direction and timing of the movement, and significantly improves the dynamic obstacle avoidance performance of the algorithm. The dynamic obstacle simulation test verifies that the algorithm has high real-time and strong path planning ability. After that, the unmanned boat control system is designed, and in the physical test on the lake, the unmanned boat can rely on the improved Bug2 algorithm to plan the obstacle avoidance path in time when encountering obstacles, realizing the autonomous obstacle avoidance, which provides solid technical support for intelligent navigation in the complex sea area.

Harbin Institute of Technology (CN)
Major Scientific and Technological Innovation Project of Shandong Province
Openalex Percentile: Top 72%
Robotic Path Planning Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.