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Navigating in off-road environments is a huge challenge for autonomous vehicles, due to the safety requirement, the effects of noises and non-holonomic constraints of vehicle. This paper aims to describe a path planning method based on fuzzy support vector machine (FSVM) and general regression neural network (GRNN) that is able to provide a solution path for the autonomous vehicle navigating in the off-road environments.

The authors decompose the path planning problem into three steps. In the first step, A* algorithm is applied to obtain the positive and negative samples. In the second step, the authors use a learning approach based on radial basis function kernel FSVM to maximize the safety margin for driving, and the fuzzy membership is designed based on GRNN which can help to resolve the problem that the traditional path planning method is easily influenced by noises or outliers. In the third step, the Bezier interpolation algorithm is used to smooth the path. The simulations are designed to verify the parameters of the path planning algorithm.

The method is implemented on autonomous vehicle and verified against many outdoor scenes. Road test indicates that the proposed method can produce a flexible, smooth and safe path with good anti-jamming performance.

This paper applied a new path planning method based on GRNN-FSVM for autonomous vehicle navigating in off-road environments. GRNN-FSVM can reduce the effects of outliers and maximize the safety margin for driving, the generated path is smooth and safe, while satisfying the constraint of vehicle kinematic.

Wool, mainly composed of keratin, is a relatively high-grade clothing material. Although woollen textile has the advantages of high wearing comfort and excellent warmth retention property as we have known, its inherent disadvantage of easy pilling has easy puzzled people for a long time. Most of the existing technologies for pilling resistance are not eco-friendly or severely damaged the internal structure of wool.

In this work, a controlled and effective surface treatment method was proposed to controllable micro-dissolution the scale layers of wool with minor damage to its internal structure, thereby improving the anti-pilling property of wool. Thiourea dioxide (TD) is used as a dissolving agent to swell and dissolve wool surface flakes. After TD treatment, the morphology changes of wool fibers were observed by scanning electron microscope (SEM) and methylene blue staining. Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) were used to characterize the structural changes of TD wool. At the same time, the anti-pilling properties and wettability of wool fabrics were tested.

The results show that the wool scale layer is destroyed after TD treatment, which reduces the friction between fibers and improves the anti-pilling performance of wool fabrics. The methylene blue-stained images further demonstrate that low concentrations of TD can damage the superficial scale layer of wool without significant loss of strength.

This method is simple, eco-friendly and economical, and opens up a new direction for the surface treatment of wool fabrics.

The purpose of this paper is to discuss the Schur D‐stability and the vertex stability of interval matrices (including point matrix obviously). Some new sufficient conditions (criteria) are proposed which guarantee the interval matrix is Schur D‐stable. This results are shown to be less conservative than those in recent literatures. In addition, two equivalence relations between the Schur D‐stability and the vertex stability of interval matrices will be proposed and a new Schur D‐stability range of an interval matrix presented.

Matrix eigenvalues theory and matrix measure approach.

Several simple sufficient conditions (criteria) for guaranteeing the Schur D‐stability of interval matrices are derived, two equivalence relations between the Schur D‐stability and the vertex stability of interval matrices are proposed, and a new Schur D‐stability range of an interval matrix is presented.

Control theory or stability theory. These stability criterion possess simple forms and provide useful tools to check Schur D‐stability of interval matrices (including point matrix) at first stage.

The paper provides useful tools to check Schur D‐stability of interval matrices (including point matrix) at first stage.

Two equivalence relations between the Schur D‐stability and the vertex stability for general interval matrices (including point matrix) are proposed, such that the conditional limitations for tridiagonal matrix in recent papers are broken. A new Schur D‐stability range of an interval matrix is presented, and several simple sufficient conditions are obtained which guarantee the Schur D‐stability of interval matrices (including point matrix).