Development of a stable localized visual inspection system for underwater structures

To avert potential crisis from Japan’s aging infrastructure and declining birth rate, the Japanese Government is planning to introduce robotic technology for the inspection of social infrastructure (such as pipes, dams, and bridges). Recording underwater positions is a difficult task for human divers who undertake conventional dam inspections. This study presents the Anchor Diver 5.2 system for efficient and effectual dam inspection. Anchor Diver 5.2 is based on an extended-tether-maneuvered remotely operated vehicle (ROV) equipped with cameras. The ROV is lowered into water by a hoist system from a boat and implements a visual survey of the concrete underwater structure. To improve the visibility of the ROV in murky and cloudy water, a novel concept named Water Loupe is proposed. In addition, a simple boat-fixing method is proposed to provide a stable base on the water surface, and the underwater position of the ROV, which cannot be accessed by global positioning systems, is recorded using a feasible localization method. Finally, the developed system was evaluated in field experiments conducted in the Amagase Dam, Japan, and its merits and problems are discussed.     

Set‐based fault detection and isolation for detectable linear parameter‐varying systems

In the context of fault detection and isolation of linear parameter‐varying systems, a challenging task appears when the dynamics and the available measurements render the model unobservable, which invalidates the use of standard set‐valued observers. Two results are obtained in this paper, namely, using a left‐coprime factorization, one can achieve set‐valued estimates with ultimately bounded hyper‐volume and convergence dependent on the slowest unobservable mode; and by rewriting the set‐valued observer equations and taking advantage of a coprime factorization, it is possible to have a low‐complexity fault detection and isolation method. Performance is assessed through simulation, illustrating, in particular, the detection time for various types of faults. Copyright © 2017 John Wiley & Sons, Ltd.     

Supporting Unified Distributed Management and Autonomic Decisions: Design,Implementation and Deployment

Nowadays, the prevailing use of networks based on traditional centralized management systems reflects on a fast increase of the management costs. The growth in the number of network equipments and services reinforces the need to distribute the management responsibilities throughout the network devices. In this approach, each device executes common network management functionalities, being part of the overall network management platform. In this paper, we present a Unified Distributed Network Management (UDNM) framework that provides a unified (wired and wireless) management network solution, where further different network services can take part of this infrastructure, e.g., flow monitoring, accurate routing decisions, distributed policies dissemination, etc. This framework is divided in two main components: (A) Situation awareness, which sets up initial information through bootstrapping, discovery, fault-management process and exchange of management information; (B) Autonomic Decision System (ADS) that performs distributed decisions in the network with incomplete information. We deploy the UDNM framework in a testbed which involves two cities (\(\approx\)250 km between), different standards (IEEE 802.3, IEEE 802.11 and IEEE 802.16e) and network technologies, such as, wired virtual grid, wireless ad-hoc gateways, ad-hoc mobile access devices. The UDNM framework integrates management functionalities into the managed devices, proving to be a lightweight and easy-respond framework. The performance analysis shows that the UDNM framework is feasible to unify devices management functionalities and to take accurate decisions on top of a real network.     

On the constraints violation in forward dynamics of multibody systems

It is known that the dynamic equations of motion for constrained mechanical multibody systems are frequently formulated using the Newton–Euler’s approach, which is augmented with the acceleration constraint equations. This formulation results in the establishment of a mixed set of partial differential and algebraic equations, which are solved in order to predict the dynamic behavior of general multibody systems. The classical solution of the equations of motion is highly prone to constraints violation because the position and velocity constraint equations are not fulfilled. In this work, a general and comprehensive methodology to eliminate the constraints violation at the position and velocity levels is offered. The basic idea of the described approach is to add corrective terms to the position and velocity vectors with the intent to satisfy the corresponding kinematic constraint equations. These corrective terms are evaluated as a function of the Moore–Penrose generalized inverse of the Jacobian matrix and of the kinematic constraint equations. The described methodology is embedded in the standard method to solve the equations of motion based on the technique of Lagrange multipliers. Finally, the effectiveness of the described methodology is demonstrated through the dynamic modeling and simulation of different planar and spatial multibody systems. The outcomes in terms of constraints violation at the position and velocity levels, conservation of the total energy and computational efficiency are analyzed and compared with those obtained with the standard Lagrange multipliers method, the Baumgarte stabilization method, the augmented Lagrangian formulation, the index-1 augmented Lagrangian, and the coordinate partitioning method.     

A dynamic default revision mechanism for speculative computation

In this work a default revision mechanism is introduced into speculative computation to manage incomplete information. The default revision is supported by a method for the generation of default constraints based on Bayesian networks. The method enables the generation of an initial set of defaults which is used to produce the most likely scenarios during the computation, represented by active processes. As facts arrive, the Bayesian network is used to derive new defaults. The objective with such a new dynamic mechanism is to keep the active processes coherent with arrived facts. This is achieved by changing the initial set of default constraints during the reasoning process in speculative computation. A practical example in clinical decision support is described.     

Analyses and improvement of a broadcasting multiple blind signature scheme based on quantum GHZ entanglement

A broadcasting multiple blind signature scheme based on quantum GHZ entanglement has been presented recently. It is said that the scheme’s unconditional security is guaranteed by adopting quantum key preparation, quantum encryption algorithm and quantum entanglement. In this paper, we prove that each signatory can get the signed message just by an intercept–resend attack. Then, we show there still exist some participant attacks and external attacks. Specifically, we verify the message sender Alice can impersonate each signatory to sign the message at will, and so is the signature collector Charlie. Also, we demonstrate that the receiver Bob can forge the signature successfully, and with respect to the external attacks, the eavesdropper Eve can modify the signature at random. Besides, we discover Eve can change the signed message at random, and Eve can impersonate Alice as the message sender without being discovered. In particular, we propose an improved scheme based on the original one and show that it is secure against not only the attacks mentioned above but also some collusion attacks.     

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.     

Randomization can be a healer: consensus with dynamic omission failures

Wireless ad-hoc networks are being increasingly used in diverse contexts, ranging from casual meetings to disaster recovery operations. A promising approach is to model these networks as distributed systems prone to dynamic communication failures. This captures transitory disconnections in communication due to phenomena like interference and collisions, and permits an efficient use of the wireless broadcasting medium. This model, however, is bound by the impossibility result of Santoro and Widmayer, which states that, even with strong synchrony assumptions, there is no deterministic solution to any non-trivial form of agreement if n ? 1 or more messages can be lost per communication round in a system with n processes. In this paper we propose a novel way to circumvent this impossibility result by employing randomization. We present a consensus protocol that ensures safety in the presence of an unrestricted number of omission faults, and guarantees progress in rounds where such faults are bounded by ${f \,{\leq}\,\lceil \frac{n}{2} \rceil (n\,{-}\,k)\,{+}\,k\,{-}\,2}$ , where k is the number of processes required to decide, eventually assuring termination with probability 1.     

Towards human motion capture from a camera mounted on a mobile robot

This article describes a multiple feature data fusion applied to a particle filter for marker-less human motion capture (HMC) by using a single camera devoted to an assistant mobile robot. Particle filters have proved to be well suited to this robotic context. Like numerous approaches, the principle relies on the projection of the model's silhouette of the tracked human limbs and appearance features located on the model surface, to validate the particles (associated configurations) which correspond to the best model-to-image fits. Our particle filter based HMC system is improved and extended in two ways. First, our estimation process is based on the so-called AUXILIARY scheme which has been surprisingly seldom exploited for tracking purpose. This scheme is shown to outperform conventional particle filters as it limits drastically the well-known burst in term of particles when considering high dimensional state-space. The second line of investigation concerns data fusion. Data fusion is considered both in the importance and measurement functions with some degree of adaptability depending on the current human posture and the environmental context encountered by the robot. Implementation and experiments on indoor sequences acquired by an assistant mobile robot highlight the relevance and versatility of our HMC system. Extensions are finally discussed.     

<Emphasis Type="Italic">hp</Emphasis>-Version <Emphasis Type="Italic">a priori</Emphasis> Error Analysis of Interior Penalty Discontinuous Galerkin Finite Element Approximations to the Biharmonic Equation

We consider the symmetric formulation of the interior penalty discontinuous Galerkin finite element method for the numerical solution of the biharmonic equation with Dirichlet boundary conditions in a bounded polyhedral domain in . For a shape-regular family of meshes consisting of parallelepipeds, we derive hp-version a priori bounds on the global error measured in the L² norm and in broken Sobolev norms. Using these, we obtain hp-version bounds on the error in linear functionals of the solution. The bounds are optimal with respect to the mesh size h and suboptimal with respect to the degree of the piecewise polynomial approximation p. The theoretical results are confirmed by numerical experiments, and some practical applications in Poisson–Kirchhoff thin plate theory are presented.