[1]罗小元,葛尚博,闫敬.障碍物与多目标约束下主动传感器网络自组织运动规划[J].燕山大学学报,2018,42(2):168-176.[doi:10.3969/j.issn.1007-791X.2018.02.011]
 LUO Xiaoyuan,GE Shangbo,YAN Jing.Self-organized motion planning of active sensor networks with obstacle and multi-objective constraints[J].Journal of YanShan University,2018,42(2):168-176.[doi:10.3969/j.issn.1007-791X.2018.02.011]
点击复制

障碍物与多目标约束下主动传感器网络自组织运动规划
分享到:

《燕山大学学报》[ISSN:1007-791X/CN:13-1219/N]

卷:
42
期数:
2018年第2期
页码:
168-176
栏目:
计算机与控制工程
出版日期:
2018-03-31

文章信息/Info

Title:
Self-organized motion planning of active sensor networks with obstacle and multi-objective constraints
文章编号:
1007-791X(2018)02-0168-09
作者:
罗小元*葛尚博闫敬
燕山大学 电气工程学院,河北 秦皇岛 066004
Author(s):
LUO XiaoyuanGE ShangboYAN Jing
School of Electrical Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China
关键词:
主动传感器网络自组织拍卖算法运动规划快速扩展随机树
Keywords:
active sensor network self-orgnization auction algorithm motion planning rapidly-exploring random tree
分类号:
TP27
DOI:
10.3969/j.issn.1007-791X.2018.02.011
文献标志码:
A
摘要:
为解决障碍物环境与多目标约束下主动传感器网络自组织运动规划问题,提出了一种分阶段无碰撞运动规划方法。首先,将目标价值及距离代价转化为收益,以系统收益最大为目标,设计了一种基于拍卖算法的多目标选择机制。在每个传感器节点选择各自目标基础上,提出一种改进的快速扩展随机树算法。相比于传统的快速扩展随机树算法,所提出的改进算法引入了启发式函数,减少了不必要的轨迹路径,进而降低轨迹规划时间。最后,给出了主动传感器网络在不同障碍环境下的规划路径,验证了所提算法的优越性。
Abstract:
In order to solve the problem of motion planning for self-organization of an active sensor network under the constraints of obstacle environment and multi-target,a collision-free path planning algorithm is presented in the paper.Firstly,a multi-objective selection mechanism based on auction algorithm is designed to convert the target value and the distance cost into profits,which achieves the goal of maximizing the system benefits.An improved rapidly-exploring random tree (RRT) algorithm is proposed for each sensor node based on its own target.Compared with the traditional RRT algorithm,the improved RRT algorithm introduces a heuristic evaluation function to reduce some needless trajectory paths and reduces the path planning time.Finally,under different obstacle environments,the simulations of the path planning of the active sensor networks are provided to verify the superiority of the proposed algorithms.

备注/Memo

备注/Memo:
收稿日期:2017-04-17        责任编辑:孙峰
基金项目:国家自然科学基金资助项目(61375105)
作者简介: *罗小元(1976-),男,江西吉安人,博士,教授,博士生导师,主要研究方向为多自主体协调控制、无线传感器网络, Email:xyluo@ysu.edu.cn
更新日期/Last Update: 2018-07-13