检索结果-内蒙古大学图书馆

Gait optimization and energy-based stability for biped locomotion using large-scale programming

ROBOTICA 2023年第7期41卷 2207-2227页

作者： Xie, Ye Gao, Chengzhi Zhu, Shiqiang Yan, Xufei Kong, Lingyu Xie, Anhuan Gu, Jason Zhang, Dan Zhejiang Lab Intelligent Robot Res Ctr Hangzhou 311100 Zhejiang Peoples R China Zhejiang Univ Hangzhou 311100 Zhejiang Peoples R China Dalhousie Univ Halifax NS B3H 4R2 Canada York Univ Toronto ON M3J 1P3 Canada

This paper presents a gait optimization method to generate the locomotion pattern for biped and discuss its stability. The main contribution of this paper is a newly proposed energy-based stability criterion, which permits the dynamic stable walking and could be straight-forwardly generalized to different locomotion scenarios and biped robots. The gait optimization problem is formulated subject to the constraints of the whole-body dynamics and kinematics. The constraints are established based on the modelling of bipedal hybrid dynamical systems. Following the whole-body modelling, the system energy is acquired and then applied to create the stability criterion. The optimization objective is also established on the system energy. The gait optimization is solved by being converted to a large-scale programming problem, where the transcription accuracy is improved via the spectral method. To further reduce the dimensionality of the large-scale problem, the whole-body dynamics is re-constructed. The generalization of the optimized gait is improved by the design of feedback control. The optimization examples demonstrate that the stability criterion naturally leads to a cyclic biped locomotion, though the periodicity was not previously imposed. Two simulation cases, level ground walking and slope walking, verify the generalization of the stability criterion and feedback control. The stability analyses are carried out by investigating the motions of centre of gravity and centre of pressure. It is revealed that if the tracked speed is above 0.3 m/s or the biped accelerates/climbs the slope, the stability criterion accomplishes the dynamic stable walking, where zero moment point criterion is not strictly complied.

关键词： bipeds hybrid dynamics gait optimization stability large-scale programming

来源：评论

学校读者我要写书评

暂无评论

A FUZZY DUAL DECOMPOSITION METHOD FOR large-scale MULTIOBJECTIVE NONLINEAR-programming PROBLEMS

引用

FUZZY SETS AND SYSTEMS 1994年第1期67卷 19-27页

作者： SAKAWA, M YANO, H NAGOYA MUNICIPAL WOMENS COLL NAGOYA 464JAPAN

In this paper, we propose a fuzzy dual decomposition method for large-scale multiobjective nonlinear programming problems (LS-MONLPs) with the block angular structure. By considering the vague nature of human judgements, we assume that the decision maker (DM) may have a fuzzy goal for each of the objective functions in the LS-MONLP. After eliciting the corresponding membership function for each of the objective functions through the interaction with the DM, an extended primal problem and the corresponding extended dual problem are formulated. Then a two-level optimization algorithm for the extended dual problem is proposed for deriving the compromise solution for the DM to the LS-MONLP. Based on the proposed algorithm, FORTRAN programs are developed and an illustrative numerical example is demonstrated.

关键词： MULTIOBJECTIVE NONLINEAR programming DECISION MAKING large-scale programming DECOMPOSITION METHODS BLOCK ANGULAR STRUCTURE

来源：评论

学校读者我要写书评

暂无评论

APPLICATIONS OF THE METHOD OF PARTIAL INVERSES TO CONVEX-programming - DECOMPOSITION

引用

MATHEMATICAL programming 1985年第2期32卷 199-223页

作者： SPINGARN, JE 1.School of Mathematics Georgia Institute of Technology 30332 Atlanta GA USA

A primal–dual decomposition method is presented to solve the separable convex programming problem. Convergence to a solution and Lagrange multiplier vector occurs from an arbitrary starting point. The method is equivalent to the proximal point algorithm applied to a certain maximal monotone multifunction. In the nonseparable case, it specializes to a known method, the proximal method of multipliers. Conditions are provided which guarantee linear convergence.

关键词： Monotone Multifunction Separable Convex programming Proximal Point Algorithm Decomposition Algorithm Resource Allocation large-scale programming

来源：评论

学校读者我要写书评

暂无评论

A SPARSE SEQUENTIAL QUADRATIC-programming ALGORITHM

引用

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1989年第3期60卷 453-473页

作者： NICKEL, RH TOLLE, JW UNIV N CAROLINA CURRICULUM OPERAT RES & SYST ANALCHAPEL HILLNC 27514

Described here is the structure and theory for a sequential quadratic programming algorithm for solving sparse nonlinear optimization problems. Also provided are the details of a computer implementation of the algorithm along with test results. The algorithm maintains a sparse approximation to the Cholesky factor of the Hessian of the Lagrangian. The solution to the quadratic program generated at each step is obtained by solving a dual quadratic program using a projected conjugate gradient algorithm. An updating procedure is employed that does not destroy sparsity.

关键词： Sequential quadratic programming large-scale programming nonlinear programming incomplete Cholesky factorization quadratic programming dual methods

来源：评论

学校读者我要写书评

暂无评论

Epsilon-proximal decomposition method

引用

MATHEMATICAL programming 2004年第1期99卷 89-108页

作者： Ouorou, A France Telecom R&D DACOAT F-92794 Issy Les Moulineaux 9 France

We propose a modification of the proximal decomposition method investigated by Spingarn [30] and Mahey et al. [19] for minimizing a convex function on a subspace. For the method to be favorable from a computational point of view, particular importance is the introduction of approximations in the proximal step. First, we couple decomposition on the graph of the epsilon-subdifferential mapping and cutting plane approximations to get an algorithmic pattern that falls in the general framework of Rockafellar inexact proximal-point algorithms [26]. Recently, Solodov and Svaiter [27] proposed a new proximal point-like algorithm that uses improved error criteria and an enlargement of the maximal monotone operator defining the problem. We combine their idea with bundle mecanism to devise an inexact proximal decomposition method with error condition which is not hard to satisfy in practice. Then, we present some applications favorable to our development. First, we give a new regularized version of Benders decomposition method in convex programming called the proximal convex Benders decomposition algorithm. Second, we derive a new algorithm for nonlinear multicommodity flow problems among which the message routing problem in telecommunications data networks.

关键词： convex optimization proximal point algorithms cutting planes decomposition multicommodity flows large-scale programming

来源：评论

学校读者我要写书评

暂无评论

APPROXIMATIONS IN PROXIMAL BUNDLE METHODS AND DECOMPOSITION OF CONVEX-PROGRAMS

引用

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1995年第3期84卷 529-548页

作者： KIWIEL, KC Systems Research Institute Warsaw Poland

A proximal bundle method is presented for minimizing a nonsmooth convex function f. At each iteration, it requires only one approximate evaluation of f and its epsilon-subgradient, and it finds a search direction via quadratic programming. When applied to the Lagrangian decomposition of convex programs, it allows for inexact solutions of decomposed subproblems;yet, increasing their required accuracy automatically, it asymptotically finds both the primal and dual solutions. It is an implementable approximate version of the proximal point algorithm. Some encouraging numerical experience is reported.

关键词： NONDIFFERENTIABLE OPTIMIZATION NONSMOOTH OPTIMIZATION CONVEX programming DECOMPOSITION large-scale programming PROXIMAL BUNDLE METHODS

来源：评论

学校读者我要写书评

暂无评论

Convergent Lagrangian heuristics for nonlinear minimum cost network flows

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2008年第2期189卷 324-346页

作者： Larsson, Torbjoern Marklund, Johan Olsson, Caroline Patriksson, Michael Chalmers Dept Math Sci SE-41296 Gothenburg Sweden Univ Gothenburg Dept Math Sci SE-41296 Gothenburg Sweden Linkoping Univ Dept Math SE-58183 Linkoping Sweden Lund Univ Dept Ind Management & Logist SE-22100 Lund Sweden Univ Gothenburg Dept Radio Phys SE-41345 Gothenburg Sweden

We consider the separable nonlinear and strictly convex single-commodity network flow problem (SSCNFP). We develop a computational scheme for generating a primal feasible solution from any Lagrangian dual vector;this is referred to as "early primal recovery". It is motivated by the desire to obtain a primal feasible vector before convergence of a Lagrangian scheme;such a vector is not available from a Lagrangian dual vector unless it is optimal. The scheme is constructed such that if we apply it from a sequence of Lagrangian dual vectors that converge to an optimal one, then the resulting primal (feasible) vectors converge to the unique optimal primal flow vector. It is therefore also a convergent Lagrangian heuristic, akin to those primarily devised within the field of combinatorial optimization but with the contrasting and striking advantage that it is guaranteed to yield a primal optimal solution in the limit. Thereby we also gain access to a new stopping criterion for any Lagrangian dual algorithm for the problem, which is of interest in particular if the SSCNFP arises as a subproblem in a more complex model. We construct instances of convergent Lagrangian heuristics that are based on graph searches within the residual graph, and therefore are efficiently implementable;in particular we consider two shortest path based heuristics that are based on the optimality conditions of the original problem. Numerical experiments report on the relative efficiency and accuracy of the various schemes. (C) 2007 Elsevier B.V. All rights reserved.

关键词： convex programming network flows large-scale programming

来源：评论

学校读者我要写书评

暂无评论

DECOMPOSITION OF CONVEX SIMPLEX METHOD

引用

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1975年第5-6期16卷 399-407页

作者： HSIA, WS UNIV ALABAMA DEPT MATHUNIVERSITYAL 35486

Rutenberg (Ref. 1) provided a decomposition method to solve the problem of minimizing a separable, nonlinear objective function with large-scale linear constraints by using the convex simplex method (Ref. 2). However, there seem to be some errors in his paper (Ref. 3). This paper will rebuild the method by using more convenient and consistent notation.

关键词： Decomposition methods convex programming large-scale programming

来源：评论

学校读者我要写书评

暂无评论

MATRIX AUGMENTATION AND STRUCTURE PRESERVATION IN LINEARLY CONSTRAINED CONTROL-PROBLEMS

引用

MATHEMATICAL programming 1980年第1期18卷 7-15页

作者： BISSCHOP, J MEERAUS, A World Bank Development Research Center Washington D.C. USA

Matrix augmentation is used for the inversion of bases associated with large linearly constrained control problems. It is shown how an efficient data structure can be maintained by keeping all state variables in the basis, and then nullifying some of them explicitly by using additional constraints. The proposed methodology, together with a basis updating scheme based on augmentation, forms the skeleton for an in-core algorithm using either the revised simplex method or the generalized reduced gradient method.

关键词： large-scale programming Linear Control Problems Matrix Modifications Partitioning Methods Basis Inversion

来源：评论

学校读者我要写书评

暂无评论

MATRIX AUGMENTATION AND PARTITIONING IN UPDATING OF BASIS INVERSE

引用

MATHEMATICAL programming 1977年第3期13卷 241-254页

作者： BISSCHOP, J MEERAUS, A WORLD BANK DEV RES CTRWASHINGTONDC 20431

A compact and flexible updating procedure using matrix augmentation is developed. It is shown that the representation of the updated inverse does not grow monotonically in size, and may actually decrease during certain simplex iterations. Angular structures, such as GUB, are handled naturally within the partitioning framework, and require no modifications of the simplex method.

关键词： large-scale programming Basis updating Matrix modifications Partitioning methods

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：