摘要
针对一类移动机器人航迹推算系统的故障诊断问题,提出一种多模态进化Rao-Blackwellized粒子滤波器(MERBPF)算法.为解决由粒子贫乏引起的不一致性问题,采用交叉与变异种群策略优化,根据粒子多样性加入扰动因子.利用专家规则判定机器人运动状态所对应的MERBPF,构造复杂逻辑表述方法.仿真实验结果表明:在强过程噪声下,MERBPF仍具有较高的鲁棒性,提高了诊断机器人航迹推算系统的准确率.
A multi-modality evolutionary Rao-Blackwellized particle filter（MERBPF） algorithm is proposed for mobilerobot fault diagnosis of dead reckoning system.The inconsistency from particle degeneration problem is solved by integrating swarms＇ intercross and mutation strategy and adding disturbance factors accoding to diversity.Robot moving states are determined by expert rules reasoning mechanism and monitored by each different ERBPF.Finally,the multi-modality ERBPF is formed,which expresses complex logic clearly.The experimental results show that MERBPF maintains a strong robustness even under the strong process noise,which improves the accuracy for the fault diagnosis of robot＇s dead reckoning investigation system.
出处
《控制与决策》
EI
CSCD
北大核心
2010年第12期1787-1792,共6页
Control and Decision
基金
国家自然科学基金重大专项重点项目(90820302)
