AI Article Synopsis
- MUSVs operate in unpredictable marine conditions, making collision avoidance a critical issue that needs to be addressed.
- A proposed solution is a cooperative perception framework that utilizes uncertain event detection, collision avoidance pattern recognition, and an environmental ontology model, leveraging ontology and Bayesian network theories.
- Simulated experiments demonstrated the effectiveness of this cooperative perception approach for improving MUSVs' awareness and safety in complex marine environments.
Article Abstract
Since the working environment of Multiple Unmanned Surface Vehicles (MUSVs) is accompanied by a large number of uncertainties and various hazards, in order to ensure the collision avoidance capability of MUSVs in complex marine environments, the perception of complex marine environments by MUSVs is the first problem that needs to be solved. A cooperative perception framework with uncertain event detection, cooperative collision avoidance pattern recognition and environmental ontology model is proposed to realize the cooperative perception process of MUSVs using ontology and Bayesian network theory. The cooperative perception approach was validated by simulating experiments. Results show the effectiveness of cooperative perception approach.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957737 | PMC |
| http://dx.doi.org/10.3390/s21051657 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!