AI-based path planner for an autonomous underwater vehicle
Gerardo G. Acosta, Hugo Curti, O. Calvo, Silvano Renato Rossi · 2006
This article describes the design considerations and experimental results in the implementation of the strategy to generate trajectories for an autonomous vehicle. The problem approached consists on an autonomous underwater vehicle (AUV) tracking a pipeline in the seabed. To solve this problem, a real time expert system (named EN4AUV) was developed and included in the on-board AUV central processing unit. EN4AUV takes trajectory control decisions based on a number of variables, arranged around the concept of scenarios. For different scenarios, the expert system is able to suggest trajectories. Recent trials were performed successfully in the North Sea. The article presents the full system architecture comprising the dynamic mission planner and the navigation, guidance and control systems, paying special attention to the knowledge-based path planner (KBPP) within the mission planner. Results of its performance during these sea trials are discussed.