摘要
提出了一种基于Wolfram Burgard方法改进的多机器人未知环境协作探索策略.该策略分别从以下3个方面提出相应的改进措施:为了减少重复探索区域和重探索的次数在代价值计算模型中加入了重复探索路径的影响因素;为了使各机器人始终保持通讯,在效用值计算模型中加入了有限范围通讯的影响因素;为了提高算法的实时性提出了一种全局规划与局部规划相结合的改进算法.仿真实验结果验证了该改进方法的有效性及相比于Wolfram Burgard原始方法具有以下优势:重复探索区域的重探索次数显著下降;机器人间能保持合理的间距以保证通讯不发生中断;算法的实时性有明显的提高.
An improved method for multi-robot coordinated exploration in unknown environments was proposed based on the Wolfram Burgard method. Three improvements were suggested. A factor reflecting the impact of repeated exploration of grid cells was added into the cost model, reducing repeated exploration of areas that waste exploration time. In order to maintain communication between robots, a factor for the impact of limits to the range of communication between robots was added to the utility model. An algorithm combining global planning with local planning was proposed to improve real time performance. Simulation results showed significant advantages over the Markov localization method. Time wasted in repeated exploration decreased significantly. Proper distances between robots were maintained, improving communication. Real time performance of the algorithm significantly improved.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2010年第3期371-376,共6页
Journal of Harbin Engineering University
基金
国家863计划资助项目(2006AA04Z245)
国家自然科学基金资助项目(2007AA041501)
关键词
多机器人
协作探索
全局规划
局部规划
multi-robot
coordinated exploration
global plan
local plan
