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首页> 外文期刊>Assembly Automation >Proximity query based on second order cone programming using convex superquadrics: a static collision detection algorithm for narrow-phase
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Proximity query based on second order cone programming using convex superquadrics: a static collision detection algorithm for narrow-phase

机译：基于凸超二次元的二阶锥规划的邻近查询：一种窄相静态碰撞检测算法

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摘要

Purpose - This paper aims to find an objects representation scheme with high precision and to compute the objects' separation distance effectively in final analysis. Proximity queries have been used widely in robot trajectory planning, automatic assembly planning, virtual surgery and many other applications. The core of proximity query is the precise computation of (minimum) separation distance in narrow phase, and specific object representation scheme corresponds to different methods of separation distance computation. Design/methodology/approach - In this paper, a second-order cone programming (SOCP)-based (minimum) separation distance computation algorithm was proposed. It treats convex superquadrics, descriptive primitives of complex object as the study objects. The separation distance between two convex superquadrics was written as a general nonlinear programming (NLP) problem with superquadric constraints and then transformed into an SOCP problem with the method of conic formulation of superquadric constraints. Finally, a primal-dual interior point method embedded in MOSEK was used for solving the SOCP problem. Findings - The proposed algorithm achieved exact separation distance computation between convex superquadrics, with a relative error of 10-6. It is particularly suitable for proximity queries in narrow phase of static collision detection algorithms. Further, the proposed algorithm achieved continuous collision detection between rectilinear translation superquadrics. Originality/value - The proposed algorithm in narrow phase of static collision detection algorithms makes objects' separation distance effectively computed. Proximity queries are easy and more accurate to perform in this way.
机译：目的-本文旨在找到一种高精度的对象表示方案，并在最终分析中有效地计算对象的分离距离。邻近查询已广泛用于机器人轨迹计划，自动装配计划，虚拟手术和许多其他应用程序。邻近查询的核心是在狭窄相位中精确计算（最小）分离距离，并且特定的对象表示方案对应于不同的分离距离计算方法。设计/方法/方法-在本文中，提出了一种基于二阶锥规划（SOCP）的（最小）分离距离计算算法。它把复杂对象的凸超二次元，描述性图元视为研究对象。将两个凸超二次元之间的间隔距离写为具有超二次约束的一般非线性规划（NLP）问题，然后用超二次约束的圆锥表示方法将其转化为SOCP问题。最后，使用嵌入在MOSEK中的原始对偶内点法解决了SOCP问题。发现-提出的算法实现了凸超二次之间的精确间隔距离计算，相对误差为10-6。它特别适用于静态碰撞检测算法的狭窄阶段中的邻近查询。此外，该算法实现了直线平移超二次方程之间的连续碰撞检测。创意/价值-所提出的算法在静态碰撞检测算法的狭窄阶段可以有效地计算对象的分离距离。以这种方式执行的邻近查询很容易且更准确。

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  • 来源
    《Assembly Automation》 |2015年第4期|367-375|共9页
  • 作者

    Lin Chen; Chongqi Ni; Junjie Feng; Jun Dai; Bingqiong Huang; Huaping Liu; Haihong Pan;

  • 作者单位

    College of Mechanical Engineering, Guangxi University, Guangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology, Nanning, People's Republic of China;

    College of Mechanical Engineering, Guangxi University, Nanning, People's Republic of China;

    College of Mechanical Engineering, Guangxi University, Nanning, People's Republic of China;

    College of Mechanical Engineering, Guangxi University, Nanning, People's Republic of China;

    College of Mechanical Engineering, Guangxi University, Guangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology, Nanning, People's Republic of China;

    Department of Computer Science and Technology, Tsinghua University, Beijing, People's Republic of China;

    College of Mechanical Engineering, Guangxi University, Guangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology, Nanning, People's Republic of China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Robotics; Path planning; Continuous collision detection; Proximity query; Second-order cone programming; Separation distance; Static collision detection algorithm;

    机译：机器人技术路径规划;连续碰撞检测;邻近查询;二阶锥编程;分离距离静态碰撞检测算法;

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