Hardware and software architecture for AUV based on low-cost sensors

Abstract

The use of Autonomous Underwater Vehicles (AUV) as robots for exploration and oceanology science has been a field of interest of several universities and research center's around the world in the last decade. Cuba being a country surrounded by the Caribbean Sea, having most of it's resources in it. Researchers from the Central University of Las Villas (UCLV) and the Hydrographic Research Center (HRC) have joined forces in the development of the HRC-AUV project, whit the objective of the implementation of a AUV capable to operate in the Cuban sea for exploration and supervision. The platform is based on low cost sensors and hardware. In the present document the hardware and software architectures of the AUV are presented. Also a set of experimental results are presented to validate the system.

Model-Aided Navigation with Sea Current Estimation for an Autonomous Underwater Vehicle

“…The sensors installed onboard the HRC-AUV are capable of measuring all the components of the attitude vector η L [16,19] thanks to the AHRS. The terms related to vector ν L are more complex to handle due to the high levels of drift and noise in the gyros of the AHRS and inherent errors of the INS, though they are feasible.…”

“…values for covariance matrices R and Q taken from the manufacturers information of the sensors [16,19], and as defined in Section 4, respectively. This resulted in a cross-coupling matrix, a fragment of which is presented: are heavily used in engineering and computer science applications for model parameters' estimation [32,33].…”

“…This is done in two steps. In the first step, we applied the EM algorithm to the system defined by Equation (24) and Equation (25), and estimate Q EM considering: (i) near-surface navigation, with GPS measurements (in an NED frame) replacing the INS position outputs in Equation (25) with y k = u ib ,v ib ,r,x GPS ,y GPS ,ψ c T ; and (ii) initial values for covariance matrices R and Q taken from the manufacturers information of the sensors [16,19], and as defined in Section 4, respectively. This resulted in a cross-coupling matrix, a fragment of which is presented: = 0.0007 0.0000 0.000 0.000 0.000 0.0000 0.0000 0.000 0.0003 0.0000 0.0007 0.0000 0.0000 0.000 0.0000 0.000 0.0000 0.0002 0.000 0.0000 0.0015 0.0000 0.000 0.0000 0.0000 0.0000 0.000 0.000 0.0000 0.0000 0.3510 0.1790 0.23 …”

“…), and the attitude of the vehicle (η 2 ); (ii) a GPS for surface or near-surface positioning (φ, λ); (iii) a depth sensor (P); and (iv) revolutions (n) and deflection angles for the actuator system (δ T , δ E ). All the sensor measurements are filtered and conditioned prior to their use in the INS, the DM and the autopilot [16].…”

“…In this work, we follow the recent developments of MA-INSs for underwater vehicles based on a three-DOF non-linear model [14,15] and propose a modelaided inertial navigation strategy based on the linear three-DOF DM for the HRC-AUV (a low-cost AUV under development by the Cuban Hydrographic Research Center (HRC) and the Group of Automation, Robotics and Perception (GARP) [16,17,18,19]). The proposed strategy, within a KF framework, also estimates in real-time the magnitude of the main environmental perturbation, i.e., the sea current.…”