多机器人运动目标搜索策略研究  

Research on moving-target search strategies for multiple robots

作　　者：周浦城[1] 洪炳镕[1] 蔡则苏[1] 

机构地区：[1]哈尔滨工业大学计算机科学与技术学院,黑龙江哈尔滨150001

出　　处：《哈尔滨工业大学学报》2005年第7期879-882,共4页Journal of Harbin Institute of Technology

基　　金：国家高技术研究发展计划资助项目(863-2001AA422270).

摘　　要：针对未知环境下多机器人合作搜索运动目标的问题,引入了搜索期望值和搜索增益两个概念,在此基础上提出了局部最大搜索、全局最大搜索、分区局部最大搜索以及分区全局最大搜索4种启发式搜索策略.仿真结果表明,以平均捕获时间作为评价标准,提出的几种搜索策略均明显优于随机搜索策略.In order to overcome the problem of multiple robots cooperative search for the moving targets under the unknown environment, the concepts of the searching expectation value and the searching gain are introduced. The four heuristic search strategies of local-max search, global-max search, subregional local-max search and subregional global-max search are presented. Using the average capture time as the performance metric, the proposed search strategies are tested under different simulation parameter settings. Simulation results show that the proposed search strategies far exceed the random search strategy.

关 键 词：多机器人系统 运动目标搜索 追捕-逃避问题 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]