This study is an attempt to take advantage of a cerebellar model to control a biomimetic arm. The cerebellar controller is a modified MOSAIC model which adaptively controls the arm. We call this model ORF-MOSAIC (Orga...
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ISBN:
(纸本)9781457721366
This study is an attempt to take advantage of a cerebellar model to control a biomimetic arm. The cerebellar controller is a modified MOSAIC model which adaptively controls the arm. We call this model ORF-MOSAIC (Organized by Receptive Fields MOdular Selection And Identification for control). The arm features a musculoskeletal model which is controlled through muscle activations by means of optimization techniques. With as few as 16 modules, we were able to control the arm in a workspace of 30×30 cm. The system was able to adapt to an external field as well as handling new objects despite delays. The discussion section suggests that there are similarities between the microzones in the cerebellum and the modules of this new model.
One of the crucial aspects of disaster management of emergency situations is the early assessment of needs and damages. In most disaster situations, higher fatality and increased casualty results from lack of access t...
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An algorithmic framework is developed for automatic deployment of car-like robots based on Linear Temporal Logic (LTL) formulae over a set of regions of interest in the environment. The environment and the regions of ...
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An algorithmic framework is developed for automatic deployment of car-like robots based on Linear Temporal Logic (LTL) formulae over a set of regions of interest in the environment. The environment and the regions of interest are a priori known, and the robot has non-negligible size and restricted steering capabilities. The approach relies on constructing a probabilistic finite-state abstraction of the car-like robot and on finding a trajectory (run) in this abstraction such that the probability of satisfying the LTL formula is maximized. The feasibility of our approach is supported by simulations under Matlab environment.
This paper introduces a two-stage Linear Logic based program synthesis approach to automatic RESTful web service composition. The Linear Logic theorem proof is applied at both resource and service invocation method le...
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Theoretically High-Order Sliding-Mode controllers are well suited to perform closed loop glucose regulation because they are insensitive to parameter uncertainties and robust to unknown dynamics that may perturb the s...
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ISBN:
(纸本)9781424441198
Theoretically High-Order Sliding-Mode controllers are well suited to perform closed loop glucose regulation because they are insensitive to parameter uncertainties and robust to unknown dynamics that may perturb the system. The implementation of the controller based on the concept of practical relative degree is presented. The controller was tested in Sprague-Dawley rats with steptozotocin induced diabetes. The tests demonstrated high efficacy and robustness of the controller.
A new tool has been developed for comparison and evaluation of medical images based on image registration and edge detection algorithms. The tool performance has been demonstrated on the processing of the ortopantomog...
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A new tool has been developed for comparison and evaluation of medical images based on image registration and edge detection algorithms. The tool performance has been demonstrated on the processing of the ortopantomog...
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Recently developed appearance descriptors offer the opportunity for efficient and robust facial expression recognition. In this paper we investigate the merits of the family of local binary pattern descriptors for FAC...
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Recently developed appearance descriptors offer the opportunity for efficient and robust facial expression recognition. In this paper we investigate the merits of the family of local binary pattern descriptors for FACS Action-Unit (AU) detection. We compare Local Binary Patterns (LBP) and Local Phase Quantisation (LPQ) for static AU analysis. To encode facial expression dynamics, we extend the purely spatial representation LPQ to a dynamic texture descriptor which we call Local Phase Quantisation from Three Orthogonal Planes (LPQ-TOP), and compare this with the Local Binary Patterns from Three Orthogonal Planes (LBP-TOP). The efficiency of these descriptors is evaluated by a fully automatic AU detection system and tested on posed and spontaneous expression data collected from the MMI and SEMAINE databases. Results show that the systems based on LPQ achieve higher accuracy rate than those using LBP, and that the systems that utilise dynamic appearance descriptors outperform those that use static appearance descriptors. Overall, our proposed LPQ-TOP method outperformed all other tested methods.
Abstract In this paper a new identification method for non-linear hybrid systems that have mixed continuous and discrete states by using fuzzy clustering and principal component analysis is described. The method first...
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Abstract In this paper a new identification method for non-linear hybrid systems that have mixed continuous and discrete states by using fuzzy clustering and principal component analysis is described. The method first determines the hybrid characteristic of the system inspired by an inverse form of the merge method for clusters, which makes it possible to identify the unknown switching points of a process based on just input-output data. Using the switching points, a hard partition of the input-output space is obtained. Then, we propose to use Takagi-Sugeno (TS) fuzzy models with Gaussian MFs as sub-models for each partition. Thus, the overall model is hybrid-fuzzy and will include explicitly the hybrid behavior of the system (the detected switching points) by means of binary MFs, and in each partition all the other non-linearities by means of TS sub-models. An illustrative experiment on a hybrid-tank system is conducted to present the benefits of the proposed approach.
We introduce a fast and robust subspace-based approach to appearance-based object tracking. The core of our approach is based on Fast Robust Correlation (FRC), a recently proposed technique for the robust estimation o...
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We introduce a fast and robust subspace-based approach to appearance-based object tracking. The core of our approach is based on Fast Robust Correlation (FRC), a recently proposed technique for the robust estimation of large translational displacements. We show how the basic principles of FRC can be naturally extended to formulate a robust version of Principal Component Analysis (PCA) which can be efficiently implemented incrementally and therefore is particularly suitable for robust real-time appearance-based object tracking. Our experimental results demonstrate that the proposed approach outperforms other state-of-the-art holistic appearance-based trackers on several popular video sequences.
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