摘要
多源信息融合算法主要应用于移动机器人对有害气体泄漏源的搜寻。为提高搜寻效率,用视觉传感器和嗅觉传感器共同获取环境信息,其中嗅觉传感器采用多气体传感器代替单气体传感器以提高测量的可靠性,测量位置也由单点向多点转变,并选用合适的算法分别实现各级数据的融合,最终决策移动机器人的搜寻方向。数据表明,加权平均法用于融合同类气体传感器的数据,可减小噪声和仪器故障的影响;最小二乘法可最优估计未知参数,用于反求泄漏源信息,可初步估计泄漏源的位置和流量;概率赋值方式可容纳多种信息途径共同判断泄漏源,从而更合理地确定搜寻目标。
Multi-source information fusion algorithms were used in the searching of gas leakage source in this paper. In order to improve the efficiency, gas sensors and vision sensor were mixed to get information, single gas sensor measure- ment was replaced by the multiple gas sensors, and the measurement method was changed from single-point to multi- point. In each data fusion period, some suitable algorithms are applied to determine the searching direction of the robot. The result indicates that the weighted average method used to fuse the data o{ gas sensors with same kind can reduce the influence of the noises and other troubles, the least square method which can optimally estimate unknown parame- ters can originally estimate the location and flow of the leakage, and the Bayesian inference can accumulate different in- formation source to judge the leakage,leading the robot to search the target more reasonable.
作者
邓振文
孙启湲
贾云伟
袁志千
DENG Zhen-wen SUN Qi-yuan JIA Yun-wei YUAN Zhi-qian(Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Meehatronical System, Tianjin University of Technology, Tianjin 300384, Chin)
出处
《计算机科学》
CSCD
北大核心
2016年第8期212-215,共4页
Computer Science
基金
国家自然科学基金(61201081)
天津市高等学校科技发展基金(20130704)资助
关键词
多源信息
信息融合
有害气体
泄漏源
搜寻
Multiple-source information, Information fusion, Harmful gas,Leakage source, Searching
