CAJ | 학술논문

针对移动机器人同时定位与地图创建（SLAM）系统在复杂特殊环境中应用时,单一传感器存在漏检且难以解决数据关联的问题,在多维匹配模型的基础上,提出一种多传感器数据融合模型,将数据关联问题转化为数学规划中的约束组合优化问题进行求解。实验结果表明,所提出的方法与联合相容分支定界算法（JCBB）的关联结果相当,且降低了计算代价。
침대이동궤기인동시정위여지도창건（SLAM）계통재복잡특수배경중응용시,단일전감기존재루검차난이해결수거관련적문제,재다유필배모형적기출상,제출일충다전감기수거융합모형,장수거관련문제전화위수학규화중적약속조합우화문제진행구해。실험결과표명,소제출적방법여연합상용분지정계산법（JCBB）적관련결과상당,차강저료계산대개。
When robots locate themselves in complex and hazardous environments,the simultaneous localization and mapping（SLAM） system with a single sensor might overlook some features which will lead to difficult data association.A multi-sensor based data fusion model for robotic SLAM is proposed to cope with environmental complexity by solving data association problems through combinatorial optimization on multiple data sets.Experimental results on real-world data show that our method produces data association as accurate as the joint compatibility brance and bound（JCBB） method but with reduced computing cost.