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Unmanned Surface Vehicle Simulator with Realistic Environmental Disturbances
Marcelo Paravisi1,2, Davi H Santos3, Vitor Jorge4,5
1Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul, Osório RS 95520-000, Brazil. marcelo.paravisi@acad.pucrs.br.
Robotic Unmanned Surface Vehicles (USVs) require robust navigation for disaster response. This study developed a simulation environment to model environmental forces, revealing their negative impact on USV trajectories and highlighting the need for advanced control strategies.
Area of Science:
- Robotics
- Environmental Science
- Computer Simulation
Background:
- Robotics are increasingly utilized in disaster response scenarios.
- Unmanned Surface Vehicles (USVs) face significant challenges navigating unpredictable environmental forces like waves, wind, and currents.
- Developing effective navigation strategies for USVs in harsh conditions is crucial.
Purpose of the Study:
- To present a novel simulation environment for Unmanned Surface Vehicles (USVs).
- To model the environmental forces acting on USVs in disaster scenarios.
- To provide a platform for assessing USV control strategies under various environmental disturbances.
Main Methods:
- Integration of a realistic Unmanned Surface Vehicle (USV) model with robotic middleware.
- Simulation of environmental forces including waves, wind, and water currents.
- Development of evaluation scenarios, such as bridge inspection under adverse conditions.
Main Results:
- The simulation environment successfully models environmental forces impacting USV navigation.
- Environmental forces were shown to negatively affect USV trajectories.
- The study highlights the critical need for enhanced USV control strategies.
Conclusions:
- The developed simulation environment is a valuable tool for researching USV navigation in disaster scenarios.
- Further research into USV control strategies is necessary to mitigate the effects of harsh environmental conditions.
- The findings underscore the importance of realistic modeling for advancing autonomous marine systems.
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