Mohammadreza Bayat

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.

Cooperative Control of Multiple Marine Vehicles Theoretical Challenges and Practical Issues

Abstract This paper is a brief overview of some of the theoretical and practical issues that arise in the process of developing advanced motion control systems for cooperative multiple autonomous marine vehicles (AMVs). Many of the problems addressed have been formulated in the scope of the EU GREX project, entitled Coordination and Control of Cooperating Heterogeneous Unmanned Systems in Uncertain Environments. The paper offers a concise introduction to the general problem of cooperative motion control that is well rooted in illustrative mission scenarios developed collectively by the GREX partners. This is followed by the description of a general architecture for cooperative autonomous marine vehicle control in the presence of time-varying communication topologies and communication losses. The results of simulations with the NetMar SyS (Networked Marine Systems Simulator) of ISR/IST are presented and show the efficacy of the algorithms developed for cooperative motion control. The paper concludes with a description of representative results obtained during a series of tests at sea in the Azores, in 2008.

Observability Analysis of 3D AUV Trimming Trajectories in the Presence of Ocean Currents Using Single Beacon Navigation

Abstract This paper addresses the observability properties of a 3D autonomous underwater vehicle (AUV) model in the presence of ocean currents, under the assumption that the vehicle can only measure its distance to a fixed transponder using an acoustic ranging device. In the set-up adopted, the AUV may undergo a wide range of maneuvers that are usually described as trimming trajectories. The latter are of paramount importance in flight dynamics and can be completely parametrized by three variables: i) linear body speed v, ii) flight-path angle γ, and iii) yaw rate ψ. We assume that v > 0, γ, and ψ are constant but otherwise arbitrary (within the constraints of the vehicle capabilities) and examine the observability of the resulting system with the output (measured) variable described above. We adopt weaker definitions of observability that are akin to those proposed by Herman and Krener (Hermann and Krener, 1977) but reflect the fact that we consider specific kinds of maneuvers in 3D. We show that in the presence of known constant ocean currents the 3D kinematic model of the AUV that corresponds to trimming trajectories with nonzero flight path angle and yaw rate is observable. In case the latter conditions fail, we give a complete characterization of the sets of states that are indistinguishable from a given initial state. We further show that in the case of unknown constant ocean currents the model is locally weakly observable for yaw rate different from zero but fails to be locally weakly observable for zero yaw rate. In both the cases we give a complete characterization of the sets of states that are indistinguishable from a given initial state.

An Underwater Acoustic Localisation System for Assisted Human Diving Operations

Abstract In this paper we present a solution to the problem of estimating the position and orientation of a moving underwater object using acoustic range measurements relative to moving surface objects that have access to a global navigation system. We start with the description of a standard GPS Intelligent Buoy system (GIB) that employs an Extended Kalman Filter (EKF); then we adapt this principle for the concrete task of tracking a human diver utilizing moving autonomous surface crafts. To this effect, we will introduce an advanced measurement system that improves significantly the estimation quality especially in the described scenario. The paper concludes with a short description of the first sea trials of the new developed system.

Observability Analysis of 2D Single-Beacon Navigation in the Presence of Constant Currents for Two Classes of Maneuvers

Abstract We analyze the observability properties of an underwater vehicle (moving in 2D) performing single beacon navigation for two specific classes of maneuvers, whereby the vehicle measures its distance to a fixed transponder located at a known position using an acoustic ranging device. We show that in the presence of known ocean currents, the system is found to be globally observable for constant relative course and constant (nonzero) relative course rate inputs in the sense of Herman and Krener. On the other hand, with unknown ocean currents the system fails to be locally weakly observable with constant relative course but we characterize the set of indistinguishable states from a given initial position and ocean current configuration. Interestingly, observability can be achieved with constant (nonzero) relative course rate in the presence of unknown, constant ocean currents.

Observability Analysis for AUV Range-only Localization and Mapping Measures of Unobservability and Experimental Results

Abstract We investigate the observability problem of the Simultaneous Localization and Mapping (SLAM) process of an Autonomous Underwater Vehicle (AUV) equipped with inertial sensors, a depth sensor, and an acoustic ranging device that provides relative range measurements to stationary beacons. For trimming trajectories (that is, when the motion of the AUV is in steady-state with constant linear and angular velocities expressed in the body-frame), we provide conditions under which it is possible to reconstruct the initial state of the resulting SLAM system (and in particular the position of the AUV). We show that the unobservable subspace UO restricted to the assumption that the position of one of the beacons or the initial position of the AUV is known, contains only the zero vector with exception of a distinct case where the UO is composed by a finite set of isolated points. Another problem that we also address in this paper is to understand (independently of the observer scheme) how difficult it is to accurately estimate the state of the system from the pair input/output measured signals. To this end, we compute explicitly the unobservability index and the estimation condition number that provide measures of the degree of unobservability. Simulation and experimental results with the Medusa robotic vehicle are presented and discussed.

Process Fault Detection and Diagnosis by Synchronous and Asynchronous Decentralized Kalman Filtering using State-Vector Fusion Technique

This paper addresses the problem of improving state estimation of dynamic industrial processes in real time for single, double, triple and quadruple fault detection and diagnosis purposes using multi-sensor data fusion strategy. The proposed monitoring systems track the process states to infer its operating conditions utilizing a decentralized Kalman filtering methodology based on state-vector fusion technique. The paper considers both the synchronous and asynchronous multi-sensor scenarios to explore their relevant data fusion problems. The performances of the resulting monitoring systems are investigated under the two possible cases of time-delayed measurements due to communication delay and multi-rate sensors. The state-vector data fusion technique is also adopted to integrate the individual state feature coming from the distributed extended Kalman filter (EKFs) so as to extract the necessary global detection and diagnostic information. The feasibility and effectiveness of the presented algorithms are demonstrated through simulation studies on a continuous stirred tank reactor (CSTR) benchmark problem.

Underwater localization and mapping: observability analysis and experimental results

Purpose – The authors aim to investigate the observability properties of the process of simultaneous localization and mapping of an autonomous underwater vehicle (AUV), a challenging and important problem in marine robotics, and illustrate the derived results through computer simulations and experimental results with a real AUV. Design/methodology/approach – The authors address the single/multiple beacon observability analysis of the process of simultaneous localization and mapping of an AUV by deriving the nonlinear mathematical model that describes the process; then applying a suitable coordinate transformation, and subsequently a time-scaling transformation to obtain a linear time varying (LTV) system. The AUV considered is equipped with a set of inertial sensors, a depth sensor, and an acoustic ranging device that provides relative range measurements to a set of stationary beacons. The location of the beacons does not need to be necessarily known and in that case, the authors are also interested to lo...

Online Mission Planning for Cooperative Target Tracking of Marine Vehicles

Abstract In the cooperative target tracking maneuvering a group of vehicles is required to follow a target while maintaining a desired formation in space. For that effect, the trajectory of the target has to be estimated (for example by one of the vehicles in formation), translated into mission codes (to save communication resources) and transmitted to the other vehicles. This paper addresses the online mission planning task of converting the absolute or relative position data available from the positioning system installed on the target (e.g. INS, GPS) into a set of lines and constant curvature arcs. Two algorithms are proposed: one using a polynomial fitting and a more complex one using an Interactive Multiple-Model Kalman filter. Simulation results using experimental data and a set of simulated data corrupted with noise and data loss are presented and discussed.

SLAM for an AUV using vision and an acoustic beacon

Abstract The estimation of the position and attitude of an autonomous underwater vehicle (AUV) is a challenging and important problem in marine robotics. It is well known that the underwater environment posses considerable problems, that include i) the fact that there is no GPS signal, ii) the communication is usually done through acoustic signals, which suffers from faults, delays and low bandwidth, and iii) the use of vision and/or laser is very limited due to poor visibility. In this paper, we combine a multiple set of sensors to address the full state 6DOF pose estimation of an AUV. The problem is formulated assuming that we have partial measurements from an Inertial Measurement Unit (IMU), an acoustic ranging from a single beacon buoy, and a monocular camera attached to the AUV. Using multiple model estimation techniques and the concept of Extended Kalman Filters with Simultaneous Localization and Mapping (EKF-SLAM), we propose an algorithm that integrates the AUV measurements (that arrive at different sampling-times) and compute in real time an estimate of the position and attitude of the AUV. Simulation results are presented and discussed.