Results 21  30
of
404
Cooperative localization for autonomous underwater vehicles
 IN PROC. 10TH INTERNATIONAL SYMPOSIUM ON EXPERIMENTAL ROBOTICS (ISER), RIO DE
, 2006
"... The absence of GPS underwater makes navigation for Autonomous Underwater Vehicles (AUVs) a difficult challenge. Without an external reference in the form of acoustic beacons at known positions, the vehicle has to rely on proprioceptive information obtained through a compass, a Doppler Velocity Logge ..."
Abstract

Cited by 52 (9 self)
 Add to MetaCart
(Show Context)
The absence of GPS underwater makes navigation for Autonomous Underwater Vehicles (AUVs) a difficult challenge. Without an external reference in the form of acoustic beacons at known positions, the vehicle has to rely on proprioceptive information obtained through a compass, a Doppler Velocity Logger (DVL) or an Inertial Navigation System (INS) [1]. Independent of the quality of the sensors used, the error in the position estimate based on deadreckoning information grows without bound. Typical navigation errors are 0.5 % to 2% of distance traveled for vehicles traveling within a few hundred meters of the sea floor such that their DVL has a lock on the bottom. Errors as low as 0.1 % can be obtained with large and expensive INS systems, but for vehicles relying only on a compass and a speed estimate can be as high as 10%. By surfacing the AUV can obtain a position update through its GPS, but this is impossible (under ice) or undesirable for many applications. The use of static beacons in the form of a Long Baseline (LBL) array limits the operation area to a few km 2 and requires a substantial deployment effort before operations, especially in deep water. As underwater vehicles become more reliable and affordable the simultaneous use of several AUVs recently became a viable option and multivehicle deployments will become standard in the upcoming years. This will not only make entirely new types of missions which rely on cooperation possible, but will also allow each individual member of the group to benefit from navigation information obtained from other members. For optimal cooperative localization a few dedicated Communication and Navigation AidAUVs (CNAs), which maintain an accurate estimate of their position through sophisticated DVL and INS sensors, can enable a much larger group of vehicles with less sophisticated navigation suites to maintain an accurate position, as described
Localization for largescale underwater sensor networks
, 2006
"... Abstract. In this paper, we study the localization problem in largescale underwater sensor networks. The adverse aqueous environments, the node mobility, and the large network scale all pose new challenges, and most current localization schemes are not applicable. We propose a hierarchical approach ..."
Abstract

Cited by 47 (6 self)
 Add to MetaCart
(Show Context)
Abstract. In this paper, we study the localization problem in largescale underwater sensor networks. The adverse aqueous environments, the node mobility, and the large network scale all pose new challenges, and most current localization schemes are not applicable. We propose a hierarchical approach which divides the whole localization process into two subprocesses: anchor node localization and ordinary node localization. Many existing techniques can be used in the former. For the ordinary node localization process, we propose a distributed localization scheme which novelly integrates a 3dimensional Euclidean distance estimation method with a recursive location estimation method. Simulation results show that our proposed solution can achieve high localization coverage with relatively small localization error and low communication overhead in largescale 3dimensional underwater sensor networks. 1
Randomized 3D Geographic Routing
"... Abstract—We reconsider the problem of geographic routing in wireless ad hoc networks. We are interested in local, memoryless routing algorithms, i.e. each network node bases its routing decision solely on its local view of the network, nodes do not store any message state, and the message itself can ..."
Abstract

Cited by 47 (0 self)
 Add to MetaCart
(Show Context)
Abstract—We reconsider the problem of geographic routing in wireless ad hoc networks. We are interested in local, memoryless routing algorithms, i.e. each network node bases its routing decision solely on its local view of the network, nodes do not store any message state, and the message itself can only carry information about O(1) nodes. In geographic routing schemes, each network node is assumed to know the coordinates of itself and all adjacent nodes, and each message carries the coordinates of its target. Whereas many of the aspects of geographic routing have already been solved for 2D networks, little is known about higherdimensional networks. It has been shown only recently that there is in fact no local memoryless routing algorithm for 3D networks that delivers messages deterministically. In this paper, we show that a cubic routing stretch constitutes a lower bound for any local memoryless routing algorithm, and propose and analyze several randomized geographic routing algorithms which work well for 3D network topologies. For unit ball graphs, we present a technique to locally capture the surface of holes in the network, which leads to 3D routing algorithms similar to the greedyfacegreedy approach for 2D networks. I.
Stateoftheart in protocol research for underwater acoustic sensor networks
 In Underwater Networks
, 2006
"... In this paper, architectures for twodimensional and threedimensional underwater sensor networks are discussed. A detailed overview on the current solutions for medium access control, network, and transport layer protocols are given and open research issues are discussed. Categories and Subject Des ..."
Abstract

Cited by 43 (0 self)
 Add to MetaCart
(Show Context)
In this paper, architectures for twodimensional and threedimensional underwater sensor networks are discussed. A detailed overview on the current solutions for medium access control, network, and transport layer protocols are given and open research issues are discussed. Categories and Subject Descriptors:
Beyond Trilateration: On the Localizability of Wireless Adhoc Networks
"... Abstract — The proliferation of wireless and mobile devices has fostered the demand of context aware applications, in which location is often viewed as one of the most significant contexts. Classically, trilateration is widely employed for testing network localizability; even in many cases it wrongl ..."
Abstract

Cited by 42 (12 self)
 Add to MetaCart
(Show Context)
Abstract — The proliferation of wireless and mobile devices has fostered the demand of context aware applications, in which location is often viewed as one of the most significant contexts. Classically, trilateration is widely employed for testing network localizability; even in many cases it wrongly recognizes a localizable graph as nonlocalizable. In this study, we analyze the limitation of trilateration based approaches and propose a novel approach which inherits the simplicity and efficiency of trilateration, while at the same time improves the performance by identifying more localizable nodes. We prove the correctness and optimality of this design by showing that it is able to locally recognize all 1hop localizable nodes. To validate this approach, a prototype system with 19 wireless sensors is deployed. Intensive and largescale simulations are further conducted to evaluate the scalability and efficiency of our design. I.
Tracking mobile nodes using RF Doppler shifts
 ACM Conference on Embedded Networked Sensor Systems (SenSys
, 2007
"... In this paper, we address the problem of tracking cooperative mobile nodes in wireless sensor networks. Aiming at a resource efficient solution, we advocate the use of sensors that maintain their location information and rely on the tracking service only when their locations change. In the proposed ..."
Abstract

Cited by 41 (9 self)
 Add to MetaCart
(Show Context)
In this paper, we address the problem of tracking cooperative mobile nodes in wireless sensor networks. Aiming at a resource efficient solution, we advocate the use of sensors that maintain their location information and rely on the tracking service only when their locations change. In the proposed approach, the tracked node transmits a signal and infrastructure nodes measure the Doppler shifts of the transmitted signal. We show that Mica2 motes can measure RF Doppler shifts with 0.2 Hz accuracy corresponding to a 0.14 m/s error in relative speed estimates using radio interferometric technique. The tracking problem is modeled as a nonlinear optimization problem and an extended Kalman filter is used to solve it accurately assuming Gaussian measurement errors. However, this approach may fail if the tracked node changes its speed or direction. We propose to update the Kalman filter state by performing constrained leastsquares optimization when a maneuver is detected. The combined approach achieves almost a 50 % accuracy improvement over the Kalman filter alone when the mobile node changes its direction and speed frequently. We describe our proofofconcept implementation of the tracking service and evaluate its performance experimentally and in simulation.
Consensus and collision detectors in wireless ad hoc networks
 In PODC
, 2005
"... Abstract In this study, we consider the faulttolerant consensus problem in wireless ad hoc networks with crashprone nodes. Specifically, we develop lower bounds and matching upper bounds for this problem in singlehop wireless networks, where all nodes are located within broadcast range of each oth ..."
Abstract

Cited by 40 (17 self)
 Add to MetaCart
(Show Context)
Abstract In this study, we consider the faulttolerant consensus problem in wireless ad hoc networks with crashprone nodes. Specifically, we develop lower bounds and matching upper bounds for this problem in singlehop wireless networks, where all nodes are located within broadcast range of each other. In a novel break from existing work, we introduce a highly unpredictable communication model in which each node may lose an arbitrary subset of the messages sent by its neighbors during each round. We argue that this model better matches behavior observed in empirical studies of these networks. To cope with this communication unreliability we augment nodes with receiverside collision detectors and present a new classification of these detectors in terms of accuracy and completeness. This classification is motivated by practical realities and allows us to determine, roughly speaking, how much collision detection capability is enough to solve the consensus problem efficiently in this setting. We consider ten different combinations of completeness and accuracy properties in total, determining for each whether consensus is solvable, and, if it is, a lower bound on the number of rounds required. Furthermore, we distinguish anonymous and nonanonymous protocolswhere &quot;anonymous &quot; implies that devices do not have unique identifiersdetermining what effect (if any) this extra information has on the complexity of the problem. In all relevant cases, we provide matching upper bounds. Our contention is that the introduction of (possibly weak) receiverside collision detection is an important approach to reliably solving problems in unreliable networks. Our results, derived in a realistic network model, provide important feedback to ad hoc network practitioners regarding what hardware (and lowlayer software) collision detection capability is sufficient to facilitate the construction of reliable and faulttolerant agreement protocols for use in realworld deployments.
Underwater Localization in Sparse 3D Acoustic Sensor Networks
 in Proceedings of INFOCOM
, 2008
"... Abstract—We study the localization problem in sparse 3D underwater sensor networks. Considering the fact that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its twodimensional counterpart via a projection technique and prove t ..."
Abstract

Cited by 39 (3 self)
 Add to MetaCart
(Show Context)
Abstract—We study the localization problem in sparse 3D underwater sensor networks. Considering the fact that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its twodimensional counterpart via a projection technique and prove that a nondegenerative projection preserves network localizability. We further prove that given a network and a constant k, all of the geometric klateration localization methods are equivalent. Based on these results, we design a purely distributed localization framework termed USP. This framework can be applied with any ranging method proposed for 2D terrestrial sensor networks. Through theoretical analysis and extensive simulation, we show that USP preserves the localizability of the original 3D network via a simple projection and improves localization capabilities when bilateration is employed. USP has low storage and computation requirements, and predictable and balanced communication overhead. Index Terms—3D underwater localization, acoustic sensor networks, network localization problem, localizability. I.
Achieving RangeFree Localization Beyond Connectivity
"... Wireless sensor networks have been proposed for many locationdependent applications. In such applications, the requirement of low system cost prohibitsmany rangebased methods for sensor node localization; on the other hand, rangefree localization depending only on connectivity may underutilize th ..."
Abstract

Cited by 38 (5 self)
 Add to MetaCart
(Show Context)
Wireless sensor networks have been proposed for many locationdependent applications. In such applications, the requirement of low system cost prohibitsmany rangebased methods for sensor node localization; on the other hand, rangefree localization depending only on connectivity may underutilize the proximity information embedded in neighborhood sensing. In response to the above limitations, this paper presents a rangefree approach to capturing a relative distancebetween1hopneighboringnodesfromtheirneighborhood orderings that serve as unique highdimensional location signatures for nodes in the network. With little overhead, the proposed design can be conveniently applied as a transparent supporting layer for many stateoftheart connectivitybased localization solutions to achieve better positioningaccuracy. Weimplementedourdesignwiththree wellknownlocalizationalgorithmsandtesteditintwotypes ofoutdoortestbedexperiments: an850footlonglinearnetwork with 54 MICAz motes, and a regular2D networkcovering an area of 10000 square feet with 49 motes. Results show that our design helps eliminate estimation ambiguity with subhop resolution, and reduces localization errors by as much as 35%. In addition, extensive simulations reveal an interestingfeature of robustnessfor our design underunevenly distributed radio propagation path loss, and confirm itseffectivenessforlargescalenetworks. Categories andSubject Descriptors
Resilient localization for sensor networks in outdoor environments
 In International Conference on Distributed Computing Systems. IEEE Computer Society
, 2005
"... The process of determining the physical locations of nodes in a wireless sensor network is known as localization. Selflocalization is critical for largescale sensor networks, because manual or assisted localization is often impractical due to time requirements, economic constraints, or inherent li ..."
Abstract

Cited by 38 (1 self)
 Add to MetaCart
(Show Context)
The process of determining the physical locations of nodes in a wireless sensor network is known as localization. Selflocalization is critical for largescale sensor networks, because manual or assisted localization is often impractical due to time requirements, economic constraints, or inherent limitations of the deployment scenarios. We propose scalable solutions for reliably localizing wireless sensor networks in environments conducive to several types of ranging errors. We follow a hybrid hardwaresoftware approach for acoustic ranging or radio interferometry to acquire internode distance measurements, and a resilient selflocalization algorithm to compute the node location estimates. The acoustic ranging method improves on previous work, extending the practical measurement range up to 35m in grassy outdoor environments, achieving a distanceinvariant median measurement error of about 1 % (33cm). The localization algorithm is based on Least Squares Scaling with soft constraints. Empirical evaluation using ranging results obtained from sensor network field experiments and simulations confirms that our approach is more resilient than multidimensional scaling (MDS) algorithms against largemagnitude ranging errors and sparse range measurements: conditions that are common in largescale outdoor sensor