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ABSTRACT: A novel adaptive algorithm is derived for sparse channel identification in the presence of Symmetric α-Stable (SαS) noise. The algorithm is based on the minimization of a new cost function, which is the sum of two terms. The first term is the distance between the previous and the current channel estimate. The distance metric is Riemannian, the same as in the improved-proportionate normalized least-mean-square (IPNLMS) algorithm, so that the sparse nature of the filter taps is taken into account. The second term depends on an appropriately defined 1-norm of the a posteriori estimation error and ensures robustness under SαS noise. The resulting algorithm, the so-called sign-IPNLMS (sIPNLMS), has linear computational complexity with respect to its filter coefficients. The superior performance of the sIPNLMS algorithm over the original IPNLMS, the recursive least-squares (RLS), and the normalized least-mean-square (NLMS) is shown by identifying two measured, sparse, underwater acoustic channels under the presence of recorded snapping shrimp ambient noise and simulated SαS noise. In addition, our proposed algorithm shows similar performance with IPNLMS under Gaussian noise and hence it becomes promising for either impulsive or non-impulsive noise environments.
OCEANS, 2011 IEEE - Spain; 07/2011
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ABSTRACT: Over the past decades, the design and development of mission based Autonomous Underwater Vehicle (AUV) continues to challenge researchers. Although AUV technology has matured and commercial systems have appeared in the market, a generic yet robust AUV command and control (C2) system still remains a key research area. This paper presents a command and control system architecture for modular AUVs. We particularly focus on the design and development of a generic control and software architecture for a single modular AUV while allowing natural extensions to multi-vehicle scenarios. This proposed C2 system has a hybrid modular-hierarchical control architecture. It adopts top-down approach in mission level decision making and task planning while utilizing bottom-up approach for navigational control, obstacle avoidance and vehicle fault detection. Each level consists of one or more autonomous agent components handling different C2 tasks. This structure provides the vehicle developers with an explicit view of the clearly defined control responsibilities at different level of control hierarchy. The resultant C2 system is currently operational on the STARFISH AUV built at the ARL of the National University of Singapore. It has successfully executed some autonomous missions during sea trials carried out around the Singapore coastal area.
Autonomous and Intelligent Systems (AIS), 2010 International Conference on; 07/2010
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M. Chitre
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ABSTRACT: Autonomous underwater vehicles (AUVs) that rely on dead reckoning suffer from unbounded localization error growth at a rate dependent on the quality (and cost) of the navigational sensors. Many AUVs surface occasionally to get a GPS position update. Alternatively underwater acoustic beacons such as long baseline (LBL) arrays are used for localization, at the cost of substantial deployment effort. The idea of cooperative localization with a few vehicles with high navigation accuracy (beacon vehicles) among a team of AUVs with poor navigational sensors has recently gained interest. Autonomous surface crafts (ASCs) with GPS, or sophisticated AUVs with expensive navigational sensors may play the role of beacon vehicles. Other AUVs are able to measure their range to these acoustically, and use the resulting information for self-localization. Since a single range measurement is insufficient for unambiguous localization, multiple beacon vehicles are usually required. In this paper, we explore the use of a single beacon vehicle to support multiple AUVs. We develop path planning algorithms for the beacon vehicle that take into account and minimize the errors being accumulated by other AUVs. We show that the generated beacon vehicle path enables the other AUVs to get sufficient information to keep their localization errors bounded over time.
Autonomous and Intelligent Systems (AIS), 2010 International Conference on; 07/2010
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ABSTRACT: We present a depth controller design for a torpedo-shaped autonomous underwater vehicle (AUV) known as STARFISH. It is common to design an AUV to be positively buoyant, so that it will float to the surface in case of power failure. However, most depth controllers are designed with a neutral buoyancy assumption by regarding the extra buoyancy as a disturbance. In this paper, we study the effect of buoyancy on both pitch and heave dynamics of an AUV, and propose a controller scheme that specifically compensates for the effect. We propose a simplified model for pitch dynamics that takes into account the buoyancy of the AUV. We identify the parameters of the model from field data from a closed loop depth maneuver. We adopt dual loop control methodology with inner pitch control loop and outer depth control loop. The inner pitch controller is designed using sliding mode control (SMC) with integrator effect to overcome a constant offset term due to positive buoyancy of the AUV. Then, a simple proportional controller is designed in the outer loop for depth control. Positive buoyancy of the vehicle will induce heave motion of the AUV. Thus, in order to maintain depth, the AUV need to be pitch down at certain angle. An adaptive feedforward controller is designed to compensate for this angle. The dual loop design with inner SMC and outer proportional control with feedforward loop was shown to be effective through experiments in both lake and sea.
OCEANS 2010 IEEE - Sydney; 06/2010
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ABSTRACT: The design of a communication system is closely linked to assumptions about the nature of the channel. A vast majority of the components of a modern communication system are implemented in software, affording us the ability to fine tune their parameters during operation. The objective for tuning the parameters could be to optimize data rates, protect against errors, minimize power, and so on. If the physics of the channel is completely known, it is possible to determine the values of these parameters for a given objective. However in practice, it is quite difficult to know the state of the channel completely. The parameters usually interact with each other, so tuning them in isolation is often not possible. We present a data driven approach for tuning the physical layer parameters of a communication link to optimize data rates, assuming the channel remains static over the course of a file transfer. Our approach does not need any knowledge of the physics of the channel. We illustrate the application of our approach in the context of an underwater communication link.
OCEANS 2010 IEEE - Sydney; 06/2010
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ABSTRACT: The use of autonomous underwater vehicles (AUVs) in various research, commercial and military applications has significantly increased in the recent years. Most AUVs available commercially tend to be complex and very expensive. With advances in recent technology, sensors with new functionality or lower cost substitutes have become available. Most existing AUV platforms do not facilitate easy integration of new or upgraded sensors. A solution to this problem is to have a modular AUV system with changeable payload sections capable of carrying different sensor to suite different missions. Modular AUVs are exceptionally useful in group mission scenarios with different AUVs carrying different sensor payloads. By having a team of modular AUVs, payloads can be easily interchanged between the AUVs to configure the team for various missions. Modular AUVs require their sections to be electrically and mechanically compatible with one another. In this paper we describe the detailed architecture of the electronics system for STARFISH AUV. The benefits of modular hardware and its advantages in developing and integrating newer sensor payloads with the base AUV are shown. The modular electronics system for STARFISH AUV has been implemented and currently being tested.
OCEANS 2008; 10/2008
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M. Chitre
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ABSTRACT: Autonomous Underwater Vehicle (AUV) technology has matured over the past few decades but commercial AUVs today remain complex, proprietary and expensive. Modularity in AUVs at a software, electronics and mechanical level allows users to configure AUVs for specific missions by only including the required components. With multiple base AUVs, users may easily configure heterogeneous teams of AUVs for collaborative missions. Modular AUVs are also easier to maintain. We expect that open-architecture AUVs with open software/hardware interfaces, changeable modules and open source components will become widely available in the future. However AUV configuration management and module compatibility are issues that arise with modularity. An initiative at the Acoustic Research Laboratory (ARL) of the National University of Singapore (NUS) has yielded an open- architecture collaborative prototype AUV known as STARFISH. The software components in this AUV are based on the DSAAV architecture. DSAAV has been designed ground up with modular AUVs in mind. In a DSAAV compliant AUV, each module provides a uniform software interface that other AUV modules can access. This interface allows configuration of the module, logging of critical information, discovery of services, access to sensor & actuator services, health monitoring and automated software update functionality. The interface is rich in functionality, yet light weight and portable to ensure that even low power micro-controllers can easily implement it. DSAAV can be implemented on any underlying communication backbone such as Ethernet, UDP/IP, etc. The software components running under DSAAV are independent of the underlying communication backbone and function without change in various AUVs and simulation environments. In this paper, we describe the basic philosophy and concepts behind DSAAV. We also outline the Application Programming Interface (API) for DSAAV compliant systems and describe its key functionality. It is our -
hope that DSAAV will be adopted and extended by other AUVs in the future.
OCEANS 2008; 10/2008
