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quadratic programming-based Approach for Autonomous Vehicle Path Planning in Space

Chinese Journal of Mechanical Engineering 2012年第4期25卷 665-673页

作者： CHEN Yang HAN Jianda WU Huaiyu State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan 430081 China Graduate School Chinese Academy of Sciences Beijing 100039 China

Path planning for space vehicles is still a challenging problem although considerable progress has been made over the past *** major difficulties are that most of existing methods only adapt to static environment instead of dynamic one,and also can not solve the inherent constraints arising from the robot body and the exterior *** address these difficulties,this research aims to provide a feasible trajectory based on quadratic programming（QP） for path planning in three-dimensional space where an autonomous vehicle is requested to pursue a target while avoiding static or dynamic ***,the objective function is derived from the pursuit task which is defined in terms of the relative distance to the target,as well as the angle between the velocity and the position in the relative velocity coordinates（RVCs）.The optimization is in quadratic polynomial form according to QP ***,the avoidance task is modeled with linear constraints in *** other constraints,such as kinematics,dynamics,and sensor range,are ***,simulations with typical multiple obstacles are carried out,including in static and dynamic environments and one of *** results indicate that the optimal trajectories of the autonomous robot in three-dimensional space satisfy the required ***,the QP model proposed in this paper not only adapts to dynamic environment with uncertainty,but also can satisfy all kinds of constraints,and it provides an efficient approach to solve the problems of path planning in three-dimensional space.

关键词： path planning in three-dimensional space obstacle avoidance target pursuit relative velocity coordinates quadratic programming

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A quadratic programming Model for Blast Scheduling

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International Journal of Minerals,Metallurgy and Materials 1999年第3期13卷 165-167页

作者： Chunyan Meng Samuel Frimpong Mingjian Zuo(Ph. D. Student (correspondent). 606-Chemical-Mineral Building. Dept of Civil and Environmental Engineering. University of Alberta. T6G 2G6.Edmonton, AB. Canada)(Associate protessor, School of Mining and Petrole 606-Chemical-Mineral Building Dept of Civil and Environmental Engineering University of Alberta Edmonton Alta. T6G 2G6 Canada School of Mining and Petroleum Engineering University of Alberta Canada Department of Mechanical Engineering University of Alberta Canada

A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' parameters are available from the geological database of the mine. The objective is to minimize the deviation of the average ore grade of blasted blocks from the standard ore grade required by the mill. Transportation ability constraint. production quantity demand constraint. minimum safety bench constraint. block size constraint and block, bench precedence constraints are considered in forming the programming model. This model has more practical objective function and reasonable constraints compared with the existing model for this kind of problems.

关键词： quadratic programming open pit mining blast scheduling mine production scheduling mathematical programming model

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A quadratic programming method for optimal degree reduction of Bézier curves with G^1-continuity

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2007年第10期8卷 1657-1662页

作者： LU Li-zheng WANG Guo-zhao Institute of Computer Graphics and lmage Processing Department of Mathematics Zhejiang University Hangzhou 310027 China

This paper presents a quadratic programming method for optimal multi-degree reduction of B6zier curves with G^1-continuity. The L2 and I2 measures of distances between the two curves are used as the objective functions. The two additional parameters, available from the coincidence of the oriented tangents, are constrained to be positive so as to satisfy the solvability condition. Finally, degree reduction is changed to solve a quadratic problem of two parameters with linear constraints. Applications of degree reduction of Bezier curves with their parameterizations close to arc-length parameterizations are also discussed.

关键词： Degree reduction Bezier curves Optimal approximation G^1-continuity quadratic programming

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Smooth free-cycle dynamic soaring in unspecified shear wind via quadratic programming

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Chinese Journal of Aeronautics 2022年第7期35卷 19-29页

作者： Haichao HONG Benedikt GRüTER Patrick PIPREK Florian HOLZAPFEL Institute of Flight System Dynamics Technical University of MunichGarching D-85748Germany

Harvesting wind energy is promising for extending long-endurance flights,which can be greatly facilitated by a flight technique called dynamic *** presented study is concerned with generating model-based trajectories with smooth control histories for dynamic soaring maneuvers exploiting wind *** desired smoothness is achieved by introducing a trigonometric series parameterization for the controls,which are formulated with respect to the normalized ***,the periodicity of the trigonometric functions is leveraged to facilitate the connection of cycles and streamline the problem *** relying on a specified wind profile,a freefinal-time quadratic programming-based control strategy is developed for the online correction of the flight trajectory,which requires only the instant wind *** and online numerical studies show the trade-off to achieve the smoothness and demonstrate the effectiveness of the proposed method in a varying wind field.

关键词： Dynamic soaring Optimal control quadratic programming Trajectory generation Trigonometric series

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An Interval Maximum Entropy Method for quadratic programming Problem

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Journal of China University of Mining and Technology 2005年第4期15卷 379-383页

作者： RUI Wen-juan CAO De-xin SONG Xie-wu School of Sciences China University of Mining ＆ Technology Xuzhou Jiangsu 221008 China

With the idea of maximum entropy function and penalty function methods, we transform the quadratic programming problem into an unconstrained differentiable optimization problem, discuss the interval extension of the maximum entropy function, provide the region deletion test rules and design an interval maximum entropy algorithm for quadratic programming problem. The convergence of the method is proved and numerical results are presented. Both theoretical and numerical results show that the method is reliable and efficient.

关键词： quadratic programming interval algorithm penalty function maximum entropy function

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MATHEMATICAL　ANALYSIS　OF　SOME　NEURAL　NETWORKS　FOR　SOLVING　LINEAR　AND　quadratic　programming

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Acta Mathematicae Applicatae Sinica 1996年第1期12卷 1-10页

作者：章祥荪 Institute of Applied Mathematics the Chinese Academy of Sciences Beijing China

Artificial neural network techniques have been introduced into the area of optimization in the recent decade. Some neural network models have been suggested to solve linear and quadratic programming problems. The Kennedy and Chua model[5] is one of these networks. In this paper results about the convergence of the model are obtained. Another related problem is how to choose a parameter value s so that the equilibrium point of the network immediately and properly approximates the original solution. Such an estimation for the parameter is given in a closed form when the network is used to solve linear programming.

关键词： Neural network linear programming quadratic programming penalty function method

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An Algorithm for Strictly Convex quadratic programming with Box Constraints

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运筹学学报(中英文) 1998年第1期2卷 8-22页

作者： XIAOJUN LIU YONG-CHANG JIAO SATORU FUJISHIGE University of Tsukuba Tsukuba 日本

We propose an efficient algorithm for solving strictly convex quadratic programs with box constraints (i.e., lower and upper bounds on each variable). our algorithm is based on the active set and the Newton method. We repeatedly compute relevant inverse matrices efficiently and, starting from an initial feasible poillt, we find an optimal solution of the problem in finitely many steps. Our experimental results show that the new algorithm is practically efficient.

关键词： quadratic programming algorithm active set method Newton method box constraints

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Neural Network for Solvin a Class of quadratic programming Problems

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The Journal of China Universities of Posts and Telecommunications 1997年第1期4卷 62-65页

作者： HuangJungliang XiaYousheng NanjingUniversityofPostsandTelecommuncations Nanjing210003P.R.China NanjingUniversityofPostsandTelec

The paper presengs a neural network for solving a class of quadratic programming *** neural network is completely stable to exact solutions and there are no parameters to ***,no analogue multipliers and dividers are r... 详细信息

关键词： neural network quadratic programming global convergence.

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On Neural Network Approach to Computing the quadratic programming Problem：a Further Study

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The Journal of China Universities of Posts and Telecommunications 1995年第2期2卷 13-17页

作者： XiaYoushen WuXinyu NanjingUniversityofPostsandTelecommunications Nanjing210003P.R.China NanjingUniversityofPostsandTele

The neural network for solving quadratic programming problem is further investigated, and theavailable stable testing condition of this method is purposed. We prove that the network, under proposed con-ditton, has a b... 详细信息

关键词： neural network quadratic programming global convergence

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Priority approach based on quadratic programming model to fuzzy preference relation

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Journal of Southeast University(English Edition) 2005年第1期21卷 108-110页

作者：徐泽水达庆利陈琦东南大学经济管理学院南京210096 解放军理工大学理学院南京210007

We investigate the decision-making problem with a finite set of alternatives,in which the decision information takes the form of a fuzzy preference relation. We develop asimple and practical approach to obtaining the priority vector of a fuzzy preference relation. Theprominent characteristic of the developed approach is that the priority vector can generally beobtained by a simple formula, which is derived from a quadratic programming model. We utilize theconsistency ratio to check the consistency of fuzzy preference relation. If the fuzzy preferencerelation is of unacceptable consistency, then we can return it to the decision maker to reconsiderstructuring a new fuzzy preference relation until the fuzzy preference relation with acceptableconsistency is obtained. We finally illustrate the priority approach by two numerical examples. Thenumerical results show that the developed approach is straightforward, effective, and can easily beperformed on a computer.

关键词： decision making fuzzy preference relation quadratic programming priority

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