A relative map approach to SLAM based on shift and rotation invariants

This paper presents a solution to the Simultaneous Localization and Mapping (SLAM) problem in the stochastic map framework based on the concept of the relative map. The idea consists in introducing a map state, which only contains relative quantities among the features invariant under shift and rotation. The estimation of this relative state is carried out through an Extended Kalman Filter. The shift and rotation invariance of the state allows us to significantly reduce the computational burden. In particular, the computational requirement is independent of the number of features. Furthermore, since the estimation process is local, it is not affected by the linearization introduced by the EKF. The cases of point features and corner features are considered. Furthermore, in the case of corners, it is considered a realistic case of an indoor environment containing structures consisting of several corners. Finally, since a relative map contains dependent elements, the information coming from all the constraints which express the elements dependency, is exploited. For this, an approximated solution with low computational requirement is proposed. Its limitation arises at the loop closure since it cannot exploit the information in this case. This is discussed in depth for the case of point features. Experimental results carried out on a real platform in our laboratory and by using the Victoria park dataset show the performance of the approach.     

A new approach to phoneme recognition by phoneme filter neural networks

This paper describes a phoneme filter neural network (PFN) approach to phoneme recognition. Most conventional speech recognition neural networks have a serious drawback: the network output values do not correspond to candidate likelihoods. The PFN is a multilayer neural network with fewer hidden units than input units prepared for each of the phoneme categories. Each network is trained as an identity mapping by speech data belonging to one phoneme category. In the recognition process, the similarity between the input data and output data is computed for each network. The results of the experiment to apply the Japanese vowel recognition task showed that the PFN recognition rates for the top two or more choices are higher than those of a conventional three-layer neural network and the PFN outputs represented candidate likelihoods. It was also confirmed that the PFN had a mapping ability and recognition performance superior to those of the linear K-L transformation method because of the nonlinearity of the PFN.     

A new multisensor fusion SLAM approach for mobile robots

This paper presents a novel method, which enhances the use of external mechanisms by considering a multisensor system, composed of sonars and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensors. To reduce ambiguity significantly, an improved and more detailed sonar model is utilized. Moreover, Hough transform is used to extract features from raw sonar data and vision image. Information is fused at the level of features. This technique significantly improves the reliability and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach.     

A new approach for constructing the concept map

In recent years, e-learning system has become more and more popular and many adaptive learning environments have been proposed to offer learners customized courses in accordance with their aptitudes and learning results. For achieving the adaptive learning, a predefined concept map of a course is often used to provide adaptive learning guidance for learners. However, it is difficult and time consuming to create the concept map of a course. Thus, how to automatically create a concept map of a course becomes an interesting issue. In this paper, we propose a Two-Phase Concept Map Construction (TP-CMC) approach to automatically construct the concept map by learners’ historical testing records. Phase 1 is used to preprocess the testing records; i.e., transform the numeric grade data, refine the testing records, and mine the association rules from input data. Phase 2 is used to transform the mined association rules into prerequisite relationships among learning concepts for creating the concept map. Therefore, in Phase 1, we apply Fuzzy Set Theory to transform the numeric testing records of learners into symbolic data, apply Education Theory to further refine it, and apply Data Mining approach to find its grade fuzzy association rules. Then, in Phase 2, based upon our observation in real learning situation, we use multiple rule types to further analyze the mined rules and then propose a heuristic algorithm to automatically construct the concept map. Finally, the Redundancy and Circularity of the concept map constructed are also discussed. Moreover, we also develop a prototype system of TP-CMC and then use the real testing records of students in junior high school to evaluate the results. The experimental results show that our proposed approach is workable.     

A new approach to solve the multi-product multi-period inventory lot sizing with supplier selection problem

This research work deals with the multi-product multi-period inventory lot sizing with supplier selection problem. Formerly, this kind of problem was formulated and solved using an exhaustive enumeration algorithm and a heuristic algorithm. In this paper, a new algorithm based on a reduce and optimize approach and a new valid inequality is proposed to solve the multi-product multi-period inventory lot sizing with supplier selection problem. Numerical experiments ratify the success of the proposed heuristic algorithm. For the set of 150 benchmark instances, including 75 small-sized instances, 30 medium-sized instances, and 45 large-sized instances, the algorithm always obtained better solutions compared with those previously published. Furthermore, according to the computational results, the developed heuristic algorithm outperforms the CPLEX MIP solver in both solution quality and computational time.     

A two-variable approach to solve the polynomial Lyapunov equation

A two-variable polynomial approach to solve the one-variable polynomial Lyapunov equation is proposed. Lifting the problem from the one-variable to the two-variable context allows to use Faddeev-type recursions in order to solve the polynomial Lyapunov equation in an iterative fashion. The method is especially suitable for applications requiring exact or symbolic computation.     

求解矩阵方程的一种新方法

如果在矩阵方程中，矩阵A是稳定矩阵，则f(P)=‖PA＋A′P＋Q‖^2→minimun。最小。本文利用该原理解矩阵方程。     

A new approach to design triplet halfband filter banks based on balanced-uncertainty optimization

This paper presents a novel approach to design a class of triplet halfband filter banks (THFB) based on optimized time–frequency localization. First, an Euler–Frobenius polynomial (EFP) is introduced to design a class of halfband polynomial. The vanishing moments and perfect reconstruction conditions are imposed on EFP to obtain maximally flat halfband filter. The resultant halfband filter is optimized using a balanced-uncertainty (BU) metric in order to have balance between time and frequency spread. Next, this optimized halfband filter is used in three-step lifting scheme to obtain analysis and synthesis wavelet filters which have balance between time and frequency localization. The proposed method provides three degrees of freedom that results in flexible design of filter bank. It is observed that the proposed filter bank gives more regularity and better frequency selectivity as compared to existing filter banks. These designed filters are then used for human chromosome image compression application. The performance of the designed filter bank is compared in terms of PSNR using different bit-rates with well-known existing filter banks in order to validate the experimental results.     

A collocation approach to solve the Riccati-type differential equation systems

In this paper, a collocation method is presented for the solutions of the system of the Riccati-type differential equations with variable coefficients. The proposed approach consists of reducing the problem to a nonlinear algebraic equation system by expanding the approximate solutions in terms of the Bessel polynomials with unknown coefficients. The unknown coefficients of the Bessel polynomials are found by using the matrix operations of derivatives together with the collocation method. The proposed method gives the analytic solutions when the exact solutions are polynomials. Also, an error analysis technique based on the residual function is introduced for the suggested method. The reliability and efficiency of the proposed scheme are demonstrated by some numerical examples. Comparing the methodology with some known techniques shows that the presented approach is relatively easy and highly accurate. All of the numerical calculations have been done by using a program written in Maple.     

A logic programming approach to cartographic map overlay

Cartographic map overlay is the process of superimposing two maps into one to convey information in spatial correlation. A map refers to one in vector representation: a two-dimensional spatial data structure of nodes, chains, and polygons. We present a map overlay system developed in Prolog. The system adopts a relational approach to data structuring. We represent geometric entities and their relationships as facts, and encode geometry algorithms in the rules. Set-based operations perform data processing. To speed up the search for chain intersections, a uniform rectangular grid is imposed over the object space for spatial sorting by distribution. We sort out potentially intersecting edge segments to those occupying some common grid cell. Each bucket, if non-empty, is implemented as a Prolog fact identifying the grid cell for random access. Geometric intersections are calculated using exact rational arithmetic implemented in Prolog. Numerical accuracy is preserved and we can identify all the special cases of tangent conditions. We can then guarantee topological consistency, and stability in the process of map overlay is therefore achieved.     

A SLAM based on auxiliary marginalised particle filter and differential evolution

FastSLAM is a framework for simultaneous localisation and mapping (SLAM) using a Rao-Blackwellised particle filter. In FastSLAM, particle filter is used for the robot pose (position and orientation) estimation, and parametric filter (i.e. EKF and UKF) is used for the feature location's estimation. However, in the long term, FastSLAM is an inconsistent algorithm. In this paper, a new approach to SLAM based on hybrid auxiliary marginalised particle filter and differential evolution (DE) is proposed. In the proposed algorithm, the robot pose is estimated based on auxiliary marginal particle filter that operates directly on the marginal distribution, and hence avoids performing importance sampling on a space of growing dimension. In addition, static map is considered as a set of parameters that are learned using DE. Compared to other algorithms, the proposed algorithm can improve consistency for longer time periods and also, improve the estimation accuracy. Simulations and experimental results indicate that the proposed algorithm is effective.     

一种适用于激光SLAM大尺度地图的闭环检测方法

针对2D激光slam在大尺度地图的闭环检测中,存在匹配候选集数量庞大和容易发生误检的问题,提出了基于子地图匹配的闭环检测方法。该方法首先使用连续几帧的激光数据构建子地图,并将构建的子地图生成压缩表,然后结合机器人的位姿估计,利用压缩表进行粗扫描匹配,筛选出闭环检测的匹配候选集, 提升匹配速度,最后用经筛选的匹配候选集进行细扫描匹配来检测闭环,以满足SLAM在大尺度地图下闭环检测的速度和准确率要求。实验结果表明,该算法可有效提高闭环检测的可靠性并显著减少匹配候选集数量。     

A New Approach to Database Auto-Design by Logic

The database auto-design is an important problem in database research.In this paper we propose some new ideas and an approach called “logic approach” to implement the database auto-design.Given a relational scheme and a set of the functional dependencies for the relation we can obtain all of the functional dependencies and key for the relation and determine the normal form the relation satisfies.     

A new policy to solve routing conflicts in shuffle-exchange networks

Batch routing is an important approach for solving routing conflicts in SE (shuffle-exchange) networks.However,the complexity of batching and the uncertainty of batch size makes this approach impracticable.Based on sequence division and routing coding concepts,we propose a method for detecting routing conflicts in an SE network,known as dividing detection that is more efficient than the method for window detection.In addition,a new conjecture relating to routing policies in SE networks is proposed.This is p...     

A sequential linear programming approach to solve mixed integer programming problems

The optimal operation of pumps in a large water supply system under time-of-use electricity rates is formulated as a mixed integer programming (MIP) problem. The problem is solved using an iterative linear programming (LP) scheme. The scheme is applied to an actual world problem, the City of Inglewood Water Supply System. Computational results are presented and termination criteria for the solution scheme are discussed.     

A prototype filter design approach to pyramid generation

This paper presents a technique for image pyramid generation, in which the reduction (expansion) factor between layers is any rational number M/L. The image pyramid generation is modeled as an interpolation and filtering followed by a decimation. The model enables frequency domain analysis of the image pyramid, as well as convenient design of the generating kernels. L(M) generating kernels are necessary to produce an image pyramid with reduction (expansion) factor M/L(L/M). A polyphase filter network scheme is used where the L(M) generating kernels can be produced by sampling one prototype low-pass filter with cutoff frequency at ω=π/max[M,L]. Using these polyphase filters, the frequency content of pyramid image decompositions can be adjusted with great flexibility. A systematic procedure is presented here for specifying the relative positions of spatial samples in successive pyramid levels-a complication that arises when generalizing from integer reduction factors to rational factors. Two types of low-pass filters are employed in this work for the prototype filter design: a binomial filter and an FIR linear phase filter. Illustrative examples are presented     

A new approach to solve the k-server problem based on network flows and flow cost reduction

This paper is concerned with two algorithms for solving the k-server problem: the optimal off-line algorithm (OPT) and the on-line work function algorithm (WFA). Both algorithms are usually implemented by network flow techniques including the flow augmentation method. In the paper a new implementation approach is proposed, which is again based on network flows, but uses simpler networks and the cost reduction method. The paper describes in detail the corresponding new implementations of OPT and WFA, respectively. All necessary correctness proofs are given. Also, experiments are presented, which confirm that the new approach assures faster execution of both algorithms.