Presence Of Unknown Ocean Currents Research Articles

Underwater docking of an under-actuated autonomous underwater vehicle: system design and control implementation

Underwater docking greatly facilitates and extends operation of an autonomous underwater vehicle (AUV) without the support of a surface vessel. Robust and accurate control is critically important for docking an AUV into a small underwater funnel-type dock station. In this paper, a docking system with an under-actuated AUV is presented, with special attention paid to control algorithm design and implementation. For an under-actuated AUV, the cross-track error can be controlled only via vehicle heading modulation, so both the cross-track error and heading error have to be constrained to achieve successful docking operations, while the control problem can be even more complicated in practical scenarios with the presence of unknown ocean currents. To cope with the above issues, a control scheme of a three-hierarchy structure of control loops is developed, which has been embedded with online current estimator/compensator and effective control parameter tuning. The current estimator can evaluate both horizontal and vertical current velocity components, based only on the measurement of AUV’s velocity relative to the ground; in contrast, most existing methods use the measurements of both AUV’s velocities respectively relative to the ground and the water column. In addition to numerical simulation, the proposed docking scheme is fully implemented in a prototype AUV using MOOS-IvP architecture. Simulation results show that the current estimator/compensator works well even in the presence of lateral current disturbance. Finally, a series of sea trials are conducted to validate the current estimator/compensator and the whole docking system. The sea trial results show that our control methods can drive the AUV into the dock station effectively and robustly.

Robust particle filter formulations with application to terrain‐aided navigation

SummaryThe work described in this paper is motivated by the need to develop efficient and robust estimation filters with application to terrain‐aided navigation of underwater robotic vehicles. One of the main problems addressed is the development of navigation particle filters that can deal with the scarcity of landmarks and the terrain ambiguity that characterize vast regions of the ocean floor. As a contribution to solve this problem, the paper proposes three novel particle filter algorithms and assesses their estimation efficiency and robustness to non‐informative measurements using two well‐known benchmarking tests. The performance of the new filters in these tests demonstrates their potential to solve a class of nonlinear problems that include, but are not limited to, the type of underwater navigation problem that motivated the present work. Our study concludes by examining the performance of the filters in terms of determining the position and velocity of an autonomous underwater vehicle in the presence of unknown ocean currents. When applied to terrain‐aided navigation, the novel particle filter formulations formulations mitigate filter divergence issues frequently caused by terrain symmetries and are more robust than other well‐known versions when used in scenarios with poor terrain information. The theoretical developments presented and the results obtained in simulations are validated using real data acquired during tests with an autonomous marine robot. Copyright © 2016 John Wiley & Sons, Ltd.

Range-Based Underwater Vehicle Localization in the Presence of Unknown Ocean Currents: Theory and Experiments

This paper addresses the problem of range-based autonomous underwater vehicle (AUV) localization in the presence of unknown ocean currents. In the setup adopted, the AUV is equipped with an attitude and heading reference system, a depth sensor, and an acoustic device that provides measurements of its distance to a set of stationary beacons. We consider the situation where the number of active beacons is not known in advance and may vary with time. The objective is to simultaneously localize the AUV and beacons, that is, to find their positions underwater. We start by deriving conditions under which it is possible to reconstruct the initial condition of the system under study. We consider the design model where the states evolve continuously with time, but the range measurements are only available at discrete instants of time, possibly in a nonuniform manner. For trimming maneuvers that correspond to AUV trajectories with constant linear and angular velocities expressed in the body frame, we show that if either the position of one of the beacons or the initial position of the AUV is known, then even without depth information the system is weakly observable (i.e., the set of states that are indistinguishable from a given initial configuration contains only a set of finite isolated points). If depth measurements are also available, then the system is observable even in the presence of unknown constant ocean currents. Equipped with these results, we then propose a novel observer for simultaneous AUV and beacon localization. The mathematical setup exploited borrows from minimum-energy estimation theory applied to continuous-time processes with discrete measurements, projection filters, and multiple-model estimation techniques. Convergence analysis of the resulting observer system yields conditions under which the estimation errors converge to a small neighborhood of the origin (whose size depends on the magnitude of the process and measurement noise). The results of field experiments with a robotic marine vehicle show the efficacy of the simultaneous AUV/multiple beacon localization system proposed.

Task space-based control of an underwater robotic system for position keeping in ocean currents

For an underwater vehicle-manipulator system, which consists of an underwater vehicle equipped with a manipulator, it is important to regulate the position of the manipulator’s end-effector with respect to a given target position in many interactive operations. This paper presents a task space-based approach for designing a controller that ensures that the end-effector of an underwater vehicle-manipulator system maintains its position in the presence of unknown ocean currents and uncertainties without the explicit use of a disturbance observer. A feedback linearizing control in task coordinates is used, and an extended Kalman filter (EKF) is employed as a state observer. The proposed approach can also be applied to dynamic positioning or controlled weathervaning of a surface ship whose motion is affected by environmental disturbances. To demonstrate the validity and effectiveness of the proposed approach, numerical simulations and experimental tests were carried out and their results are shown.

Comments on ‘Position‐tracking control of underactuated autonomous underwater vehicles in the presence of unknown ocean currents’

The control law in the commented paper is indicated to be non-causal, which cannot be applied in practical engineering directly and leads to the stability analysis incomplete. To correct the flaws, the control law is modified by solving the implicit equation in that study, and the incomplete stability analysis of the closed-loop system is finished. Finally, simulation results illustrate the effectiveness of the modified control law.

Position USBL/DVL sensor-based navigation filter in the presence of unknown ocean currents

This paper presents a novel approach to the design of globally asymptotically stable (GAS) position and velocity filters for Autonomous Underwater Vehicles (AUVs) based directly on the sensor readings of an Ultra-short Baseline (USBL) acoustic array system and a Doppler Velocity Log (DVL). The proposed methodology is based on an equivalent linear time-varying (LTV) system that fully captures the dynamics of the nonlinear system, allowing for the use of powerful linear system analysis and filtering design tools that yield GAS filter error dynamics. Numerical results using Monte Carlo simulations and comparison to the Bayesian Cramér Rao Bound (BCRB) reveal that the performance of the proposed filter is tight to this theoretical estimation error lower bound. In comparison with other approaches, the present solution achieves the same level of performance of the Extended Kalman Filter (EKF), which does not offer GAS guarantees, and outperforms other classical filtering approaches designed in inertial coordinates instead of the body-fixed coordinate frame.

Position-tracking control of underactuated autonomous underwater vehicles in the presence of unknown ocean currents

This study addresses the problem of position-tracking control of underactuated autonomous underwater vehicles (AUVs) in the presence of unknown ocean currents in a horizontal plane. A position-tracking controller and a current observer are presented based on the Lyapunov stability theory by using the backstepping technique, respectively. The final controlled system, which arises from putting together the position-tracking controller and the observer, is proved to be globally K-exponentially stable by stability criteria for cascade system. The trajectories used for the illustration of the proposed control schemes are a circle with constant velocity and a sinusoidal curve that requires time-varying velocity. In order to demonstrate the practicability of the proposed controller, the surge force is assumed to be non-negative, and control input saturations are considered. Simulation results are presented to demonstrate the effectiveness of the proposed control schemes.

Single Beacon Acoustic Navigation for an AUV in the presence of unknown ocean currents

This paper addresses the problem of underwater navigation, using a single beacon (or a transponder). We propose a solution to estimate the underwater vehicle position in the presence of unknown ocean currents. The main idea is to combine the dead-reckoning information with multiple range measurements taken at different instants of time from the vehicle to a single beacon. Then, applying a multilateration based algorithm and using a Kalman filter, the unknown velocity of ocean current and a more accurate estimation of vehicle's position is estimated. The stability and convergence of the position estimation error are analysed taken explicitly into account the presence of ocean currents, disturbances, measurement noise and discretization errors. Simulation results are presented and discussed. In particular, we show that the implementation of the Kalman filter to estimate the ocean current is crucial to achieve convergence of the estimated position.

Geophysical Navigation of Autonomous Underwater Vehicles Using Geomagnetic Information

This paper addresses the general problem of Autonomous Underwater Vehicle navigation by exploiting the availability of terrain and geophysics-related data. Geophysical navigation algorithms are derived to estimate the position and velocity of an AUV in the presence of unknown ocean currents and sensor biases. The current implementation merges acoustic and magnetic measurements with dead-reckoning data. One of the main contributions of the paper is the utilization of maps of invariant gradients that can be calculated from prior maps of the geomagnetic field. The results obtained through computer simulations with real data show the effectiveness of the GN approach proposed.

GEOPHYSICAL NAVIGATION OF AUTONOMOUS UNDERWATER VEHICLES

The paper addresses the problem of Geophysical Navigation (GN) of Autonomous Underwater Vehicles (AUVs). The objective is to use bathymetric and geomagnetic information to estimate the position and velocity of an AUV in the presence of unknown ocean currents. The navigation estimator derived mechanizes a sequential Bayesian estimation strategy consisting of a novel particle filter algorithm that we name Smooth Kernel Particle Filter. The estimator relies essentially on the AUV kinematics. It integrates measurements derived from the terrain with dead-reckoning based on Doppler and attitude sensors. Central to the strategy derived is the concept of maps of invariant gradients of the geomagnetic field as an efficient form of representing geomagnetic terrain information. The results obtained through computer simulations show the effectiveness of the GN approach proposed.