Optimal formation of robots by the continuous-discrete PSO algorithm in three dimensional space

Jun Liu, Hongbin Ma, T. Shi, Ping Li
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引用次数: 2

Abstract

This paper mainly provides and develops a new continuous-discrete PSO algorithm for handling with the optimal formation problem in the three dimensional space. For one class of formation problem with the particular constraints, it is shown that the center of the desired shape is determined and equal to the center of the initial shape by utilizing the Lagrangian method. From the perspective of efficiency, the main task of the continuous-discrete PSO algorithm, short for CDPSO, is to search for some key parameters and to minimize the distance of all robots from the initial shape to the desired shape. To demonstrate the effectiveness of the new CDPSO algorithm, numerical results chiefly concentrate on the optimal helicopters formation from the initial shape to the desired shape in the three dimensional space and the typical shape conversion from the two-dimensional space to the three-dimensional space.
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基于连续离散粒子群算法的三维机器人最优编队
本文主要提出并发展了一种新的连续离散粒子群算法来处理三维空间中的最优编队问题。对于一类具有特殊约束条件的形成问题,利用拉格朗日方法,证明了期望形状的中心是确定的,并且等于初始形状的中心。从效率的角度出发,连续离散粒子群算法(continuous-discrete PSO algorithm,简称CDPSO)的主要任务是搜索一些关键参数,使所有机器人从初始形状到期望形状的距离最小。为了验证该算法的有效性,数值结果主要集中在三维空间中由初始形状到期望形状的最优直升机编队,以及从二维空间到三维空间的典型形状转换。
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