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The operation of industrial Automated Guided Vehicles (AGV) today requires designated infrastructure and readily available maps for their localization. In logistics, high effort and investment is necessary to enable the introduction of AGVs. Within the SICK AG coordinated EU-funded research project PAN-Robots we aim to reduce the installation time and costs dramatically by semi-automated plant exploration...
The registration of 3D laser scans is an important task in mapping applications. For the task of mapping with autonomous micro aerial vehicles (MAVs), we have developed a light-weight 3D laser scanner. Since the laser scanner is rotated quickly for fast omnidirectional obstacle perception, the acquired point clouds are particularly sparse and registration becomes challenging. In this paper, we present...
Genetic changes that may be associated with complex diseases are tried to be determined by means of many genome-wide association studies. Single Nucleotide Polymorphisms (SNPs) are used primarily in these studies since they comprise a large part of these genetic changes. Statistical importance of the genome-wide association study is directly related to the number of individuals and SNPs. However,...
We present generalized hybrid surface-integral-equation formulations for three-dimensional conductors with arbitrary shapes. The proposed formulations are based on flexible applications of the electric-field integral equation and the magnetic-field integral equation with varying combinations on different regions of the given objects. As a proof of concept, we demonstrate hybrid formulations using...
Considering the facts that people access to item information more easily than to user information given user privacy, and the features of items selected by the user always imply his/her preferences, we hope to utilize item features to mine user preferences besides ratings. What is more, ratings are often linguistic labels and fuzzy set is tailor-made to represent them. Therefore, we propose a novel...
The main objective of this paper is to develop 3D point cloud alignment technique by using an improved absolute orientation algorithm based on unit quaternion. In this method, Scale Invariant Features Transform (SIFT) is used to find corresponding feature points, and Random Sample Consensus (RANSAC) is used as robust estimator to remove false matches in the point cloud group. The unit quaternion solution...
In many practical situations, we monitor a system by continuously measuring the corresponding quantities, to make sure that any abnormal deviation is detected as early as possible. Often, we do not have readily available algorithms to detect abnormality, so we need to use machine learning techniques. For these techniques to be efficient, we first need to compress the data. One of the most successful...
The colors in universe have sharp boundaries everybody is aware of specifically wherever a color starts and wherever it ends and that any color communicates the details about the targets in the scene in a much better way and that this detailed information can be used to further polish the interpretation of an imaging system. In this paper, the proposed subpixel level arrangements of spatial dependences...
Attribute reduction approach is proposed in this paper based on a modified version of the flower pollination algorithm optimization (FPA). Flower pollination algorithm (FPA) is one of recently evolutionary computation technique, inspired by the pollination process of flowers. The modified FPA algorithm adaptively balance the exploration and exploitation to quickly find the optimal solution through...
The idea of opposition-based learning was introduced 10 years ago. Since then a noteworthy group of researchers has used some notions of oppositeness to improve existing optimization and learning algorithms. Among others, evolutionary algorithms, reinforcement agents, and neural networks have been reportedly extended into their “opposition-based” version to become faster and/or more accurate. However,...
We consider hybrid formulations involving simultaneous applications of the electric-field integral equation (EFIE), the magnetic-field integral equation (MFIE), and the combined-field integral equation (CFIE) for the electromagnetic analysis of three-dimensional conductors with arbitrary geometries. By selecting EFIE, MFIE, and CFIE regions on a given object, and optimizing these regions in accordance...
Nowadays some High Level Synthesis (HLS) tools are introduced which are able to generate Hardware Description Language (HDL) codes from high level floating point arithmetic expressions for implementation on FPGAs. Before this conversion, changing the form of high level expressions usually leads to significant improvements in the final implementation in terms of accuracy, resource usage and latency...
Problems of optimal pole placement for linear time invariant systems via state feedback have been studied for several decades. The minimum gain pole exact placement problem involves obtaining a feedback matrix that will assign a certain desired set of closed-loop poles, while also minimizing the gain (matrix norm) of the feedback matrix. Numerous methodologies have appeared in the literature to address...
With multiple channels, Polarimetric SAR (PolSAR) contains abundant target information and anti-jamming ability, which can improve the ability of target discrimination and image interpretation. The classification problem of PolSAR has become one of the most urgent problems to be solved in PolSAR application with the improvement of PolSAR technology. Due to the complexity of multiple-dimensional classification,...
This paper addresses the problem of parameter optimization for Markov random field (MRF) models for supervised classification of remote sensing images. MRF model parameters generally impact on classification accuracy, and their automatic optimization is still an open issue especially in the supervised case. The proposed approach combines a mean square error (MSE) formulation with Platt's sequential...
This paper discusses Offset-free Energy-optimal Model Predictive Control (offset-free EOMPC) which is a MPC algorithm to realize time-constrained energy-optimal point-to-point motion control with high positioning accuracy for linear time-invariant (LTI) systems. The offset-free EOMPC approach is developed based on our previous research - Energy-optimal Model Predictive Control (EOMPC) - which aims...
This paper deals with fair public service system design formulated as the weighted p-median problem minimizing the total disutility, like social costs. The social costs are often proportional to the total distance travelled by all users to the nearest located service center. The above objective denoted as min-sum criterion may cause such situation that the total social costs are minimal, but the disutility...
To address the challenge of the accuracy and efficiency of the metamodel, an adaptive sequential polynomial chaos expansion (ASPCE) metamodel technique is presented. The Latin hypercube sampling (LHS) is used to obtain the initial samples. A new adaptive truncation strategy of polynomial chaos expansion (PCE) is presented for high order PCE, and the parameters are updated by global sensitivity indices...
The recent literature indicates that preserving local geometric structure of data graph becomes much more important for unsupervised feature selection and that many existing feature selection criteria essentially work in this way. Key to constructing a local geometric structure of data graph is to determine the elements of the similarity matrix from which it is derived. Thus, the performance of feature...
Thermal error accounts for a large proportion in the error sources of the machine tool. In this paper, the thermal error of a boring and milling machine tool is modeled with the output error model of timing analysis. In order to improve the prediction accuracy, Firefly algorithm is used to optimize the number of groups and the orders of output error model. A compensation system is developed based...
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