Motion planning for an autonomous underwater vehicle

This paper deals with motion planning of a REMUS autonomous underwater vehicle (AUV). It is desired to move the vehicle from the surface of the water to a depth of about two meters and then to maintain it in this depth. Therefore, real-time path trajectory is first designed based on the desired goals and then an optimal PD controller following with a proportional gain are designed to force the AUV to track the desired depth trajectory with minimum tracking error. The nonlinear model of the REMUS AUV is utilized and improved particle swarm optimization algorithm in combination with SQP method (IPSO-SQP) is used to determine the optimal value of the PD and the proportional controller parameters. The cost function is hence the tracking error and the goal is to track the desired path with minimum error.