A complete Fault Tolerant Control solution calls for a nonlinear adaptive controller with universal approximation capability and guaranteed stability. To fulfill this requirement we propose the use of Neural Networks ...
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This work proposes a gain scheduling adaptive control scheme based on fuzzy systems, neural networks and genetic algorithms for nonlinear plants. A fuzzy PI controller is developed, which is a discrete time version of...
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Attentive robots, inspired by human-like vision – are required to have visual systems with fovea-periphery distinction and saccadic motion capability. Thus, each frame in the incoming image sequence has nonuniform sa...
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Our multimodal interface integrates speech recognition, natural language understanding, spatial reasoning and human cognitive models for completing specific tasks and for perspective-taking in locative oriented tasks....
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ISBN:
(纸本)156347719X
Our multimodal interface integrates speech recognition, natural language understanding, spatial reasoning and human cognitive models for completing specific tasks and for perspective-taking in locative oriented tasks. With natural language and gestures, we believe human-robot interaction and communication is facilitated. Instead of concentrating on the various modalities of the interface, users can concentrate on the task at hand. Likewise, by incorporating human cognitive models for handling spatial information and perspective-taking, as well as for specific task completion, a better match with the expectations that humans acquire from their human-human interactions should be obtained, further facilitating cooperation and collaboration in human-robot interactions.
作者：
Jingu HeoS.G. KongB.R. AbidiM.A. AbidiImaging
Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA
This paper describes a fusion of visual and thermal infrared (IR) images for robust face recognition. Two types of fusion methods are discussed: data fusion and decision fusion. Data fusion produces an illumination-in...
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This paper describes a fusion of visual and thermal infrared (IR) images for robust face recognition. Two types of fusion methods are discussed: data fusion and decision fusion. Data fusion produces an illumination-invariant face image by adaptively integrating registered visual and thermal face images. Decision fusion combines matching scores of individual face recognition modules. In the data fusion process, eyeglasses, which block thermal energy, are detected from thermal images and replaced with an eye template. Three fusion-based face recognition techniques are implemented and tested: Data fusion of visual and thermal images (Df), Decision fusion with highest matching score (Fh), and Decision fusion with average matching score (Fa). A commercial face recognition software FaceIt® is used as an individual recognition module. Comparison results show that fusion-based face recognition techniques outperformed individual visual and thermal face recognizers under illumination variations and facial expressions.
A complete fault tolerant control solution calls for a nonlinear adaptive controller with universal approximation capability and guaranteed stability. To fulfill this requirement we propose the use of neural networks ...
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A complete fault tolerant control solution calls for a nonlinear adaptive controller with universal approximation capability and guaranteed stability. To fulfill this requirement we propose the use of neural networks trained online under a globalized dual heuristic programming architecture supervised by a decision logic capable of identifying controller malfunctions in early stages and providing new avenues with greater probability of convergence using information from a dynamic model bank. The classification and distinction of controller malfunctions and of the faults in the system is achieved through three independent quality indexes. Proof-of-the-concept simulations of nonlinear plants demonstrate the approach legitimacy
The growth of use of graph-structured databases modeled on n-partite graphs has increased the ability to generate more flexible databases. However, the calculation of certain features in these databases may be highly ...
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The growth of use of graph-structured databases modeled on n-partite graphs has increased the ability to generate more flexible databases. However, the calculation of certain features in these databases may be highly resource-consuming. This work proposes a method for approximating these features by sampling. A discussion of the difficulty of sampling in n-partite graphs is made and an evolutionary algorithm-based method is presented that uses the information from a smaller subset of the graph to infer the amount of sampling needed for the rest of the graph. Experimental results are shown on a publications database on Anthrax for finding the most important authors.
作者：
B. AbidiS. HuqM. AbidiImaging
Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA
This paper summarizes the various components of face recognition research conducted at the IRIS Lab. First, fusion of visual and thermal infrared (IR) images for robust face recognition is discussed. Two techniques ar...
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This paper summarizes the various components of face recognition research conducted at the IRIS Lab. First, fusion of visual and thermal infrared (IR) images for robust face recognition is discussed. Two techniques are implemented: data fusion and decision fusion. With the knowledge that eyeglasses block the emission of thermal energy, an algorithm is designed to detect and replace eyeglasses with an eye template in thermal images. A commercial face recognition software (FaceIt/spl reg/) is used in the evaluation of the various fusion algorithms. Comparison results show that fusion-based face recognition outperforms individual visual or thermal face recognizers under illumination variations and facial expressions. Efforts in the 3D arena are also described. Results of high resolution stereo-based 3D reconstruction of faces are shown and analyzed, in a first approach, then in a second approach, a warping technique is applied to overlay color and thermal textures on 3D mannequin head models, obtained using a laser range scanner.
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