This paper presents an novel analytical model for calculation of throughput of the IEEE 802.11 Distributed Coordination Function (DCF) under variable packet length assuming ideal channel conditions. The proposed model...
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The security of a biometric information system depends partially on the ability of the biometric information sensor to authenticate itself securely to the processing centre it usually interacts with, thus ensuring tha...
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A new fault adaptive control methodology against the actuator failure is proposed. The actuator failure modeling are introduced to denote the actuator healthy coefficients (AHCs) and the unscented Kalman filter (UKF) ...
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A new fault adaptive control methodology against the actuator failure is proposed. The actuator failure modeling are introduced to denote the actuator healthy coefficients (AHCs) and the unscented Kalman filter (UKF) is employed for on-line estimation of both the flight states and the AHCs parameters of rotorcraft UAV (RUAV). In this paper, The functionality of the approach has been illustrated through experiments on the Shenyang Institute of automation RUAV platform SIA-Heli-90 and the results show that the proposed method is an effective tool for actuator fault adaptive control of RUAVs.
A major challenge to the deployment of mobile robots is the ability to function autonomously, learning appropriate models for environmental features and adapting those models in response to environmental changes. This...
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ISBN:
(纸本)9789898111210
A major challenge to the deployment of mobile robots is the ability to function autonomously, learning appropriate models for environmental features and adapting those models in response to environmental changes. This autonomous operation in turn requires autonomous selection/planning of an action sequence that facilitates learning and adaptation. Here we focus on color modeling/learning and analyze two algorithms that enable a mobile robot to plan action sequences that facilitate color learning: a long-term action selection approach that maximizes color learning opportunities while minimizing localization errors over an entire action sequence, and a greedy/heuristic action selection approach that plans incrementally, one step at a time, to maximize the benefits based on the current state of the world. The long-term action selection results in a more principled solution that requires minimal human supervision, while better failure recovery is achieved by incorporating features of the greedy planning approach. All algorithms are fully implemented and tested on the Sony AIBO robots.
This paper presents an innovative solution in retail activities, named "Intelligent Store- INTELSHOP" based on a technological platform that offers the support for some attractive and efficient services for ...
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In this work, a solution to the problem of multi-robot following routes is proposed using an appearance-based method. In this approach, several images are stored along the route to follow, using an uncalibrated forwar...
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ISBN:
(纸本)9789898111210
In this work, a solution to the problem of multi-robot following routes is proposed using an appearance-based method. In this approach, several images are stored along the route to follow, using an uncalibrated forward-looking camera. To extract the most relevant information, an incremental PCA process has been implemented. This incremental process allows adding new locations to the PCA database without necessity of creating it from the scratch. Then, the follower robots can follow the route while a leader one is still recording it. These follower robots, using this database, make first an auto-location process to know their current position and then a control phase to compute the necessary steering speed to tend to the route and follow it till the end. Both speeds are obtained also through the visual information in an appearance-based approach. The problem of 'visual aliasing', typical in office environments, is avoided with a probabilistic approach that, using a Markov-process model, makes the localization more robust. The experimental results have shown how this is a simple but robust and powerful approach for routes in an office environment.
In this paper, we propose a locomotion control algorithm for a climbing worm robot based on neural oscillator network (NON). According to the structure and locomotion feature of the climbing worm robot, the trapezoida...
In this paper, we propose a locomotion control algorithm for a climbing worm robot based on neural oscillator network (NON). According to the structure and locomotion feature of the climbing worm robot, the trapezoidal wave gait and triangular wave gait are defined. Then the cyclic inhibitory central pattern generator (CPG) model and mutual inhibitory CPG model are adopted to control the climbing worm robot. Furthermore, by combining the CPG output with the feedback signal from the sucker, the robot realizes the trapezoidal wave gait and triangular wave gait. Moreover, we present that real robot can successfully exhibit meandering movement by using controller output of the proposed architecture.
During the late 1990s and early 2000s, the profile of global manufacturing has experienced many changes. There is anecdotal evidence that many western manufacturing companies have chosen to expand their manufacturing ...
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During the late 1990s and early 2000s, the profile of global manufacturing has experienced many changes. There is anecdotal evidence that many western manufacturing companies have chosen to expand their manufacturing base across geographical boundaries. The common reasons sited for these ventures are to exploit less expensive labour markets, to establish a presence in expanding markets and in response to the threat of new competition. Whilst a global manufacturing base can prove to have many cost and sales benefits, there are also many disadvantages. Logistics operations can often increase in complexity leading to higher reliance on planning and effective interpretation of demand data. In response, systems modelling has remerged as a fertile research area after many years. Many modelling and simulation techniques have been developed, but these have had very limited practical success. The authors have identified that majority of these simulation techniques rely upon a detailed market structure being known, when this is rarely the case. This paper describes the outcome of a research project to develop of a pragmatic set of tools to gather, assess and verify supply chain structure data. A hybrid collection of technologies are utilised to assist these operations and to build a dynamic supply network model. (C) 2007 Elsevier Ltd. All rights reserved.
Suppose that the mean μ = E[F(X)] of a given function F : → is to be estimated by the empirical average Ŝ n := 1/n∑n i=1 F(Xi) of the values F(Xi), where X1,X2, . . . , Xn are independent samples distributed like X...
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This paper deals with the actuator fault diagnosis and accommodation problem for the aero space vehicle (ASV). A novel nonlinear robust adaptive observer is developed for estimation of the actuator fault under the Lip...
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This paper deals with the actuator fault diagnosis and accommodation problem for the aero space vehicle (ASV). A novel nonlinear robust adaptive observer is developed for estimation of the actuator fault under the Lipschitz condition on the nonlinear part of such systems, which is used to continuously accommodate the control signal, so as to ensure the stability of faulty system. Finally, simulation results about ASV are presented to illustrate the feasibility and effectiveness of the proposed methods.
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