On the optimization of state observers for application in navigation of low cost autonomous vehicles
Marine Autonomous Vehicles, either Surface (ASV) or Underwater (AUV) are becoming the kingpin for ocean research and sea exploration. Long term and high persistence are highly desirable characteristics for adding to these autonomous platforms. The possibility of performing adequate tasks by using low cost underwater vehicles could multiply the number of agents in the area and therefore, providing high persistence by using multiagent relay strategies. This paper progresses in the validation of low cost electronic components for applying in the ALBA-13 AUV. Position and velocity estimation are essential for underwater vehicles because GPS signals are not available during immersion. Some works have presented theory and applications of a state observer that integrates the 6 degree-of-freedom (DOF) signals from an Inertial Measurement Unit (IMU) for estimation of position, velocity and attitude. Filtering of noisy sensor signal in combination with non-measured signal estimation is commonly addressed by the use of Linear Kalman Filters KF, Extended Kalman Filter EKF and nonlinear passive observers. The contribution of this paper is the implementation of the previously mentioned three observers and features comparison, by using low cost MEMs sensors in combination with different microcontrollers for the evaluation in low cost AUV and ASV requirements. Different tests have been simulated using MATLAB and SIMULINK and implemented on a high speed scaled boat for field validation.
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