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Decision Making in Paths of Autonomous Underwater Vehicles
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Autonomous underwater vehicles are not easily programmable such as autonomous vehicles. This is because route and motion planning for autonomous vehicles depend on a global map that considers the road's smoothness and traffic regulations in real time. However, this is not the case for underwater vehicles as we have to consider the external factors such as wind and tide that may pull autonomous underwater vehicles outside their route and affect the course of travel. This is where decision-making is important for autonomous underwater vehicles. An example is the avoidance of the loss of subsea vehicles as they can dynamically make routing decisions and return to their destinations.This paper exposes the decision-making process for autonomous underwater vehicles. Firstly, an analysis of internal factors such as buoyancy and the overall of the vehicle, and how they affect motion are conducted—secondly, the implementation of a design process that deals with the stages of motion and route planning. Finally, a survey is conducted on already implemented research for algorithms, to incorporate external factors for high-level decision-making.
Title: Decision Making in Paths of Autonomous Underwater Vehicles
Description:
Autonomous underwater vehicles are not easily programmable such as autonomous vehicles.
This is because route and motion planning for autonomous vehicles depend on a global map that considers the road's smoothness and traffic regulations in real time.
However, this is not the case for underwater vehicles as we have to consider the external factors such as wind and tide that may pull autonomous underwater vehicles outside their route and affect the course of travel.
This is where decision-making is important for autonomous underwater vehicles.
An example is the avoidance of the loss of subsea vehicles as they can dynamically make routing decisions and return to their destinations.
This paper exposes the decision-making process for autonomous underwater vehicles.
Firstly, an analysis of internal factors such as buoyancy and the overall of the vehicle, and how they affect motion are conducted—secondly, the implementation of a design process that deals with the stages of motion and route planning.
Finally, a survey is conducted on already implemented research for algorithms, to incorporate external factors for high-level decision-making.
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