基于改进IMM-UKF算法的一种融合航迹推演的红外路标室内定位方法

在结构化环境中,针对室内机器人导航对精度和实时性的要求,在一种新型红外路标定位方法的基础上,为满足全局导航的需要并简化硬件结构,提出一种融合航迹推演的红外路标室内定位方法,将单个大功率红外发射管作为路标,移动机器人上的红外摄像头作为接收传感器,融合采用改进的交互多模型无迹卡尔曼滤波(interacting multiple models unscented Kalman filter,IMM-UKF)算法.将融合航迹推演的红外路标室内定位方法和一般的定位方法做了比较,并将融合所采用改进的IMM-UKF算法与一般的融合算法做了比较.实验结果表明,提出的基于改进IMM-UKF算法的融合航迹推演的红外路标室内定位方法获得了比一般的定位方法更快的定位速度和更高的定位精度,且改进IMM-UKF算法比一般融合算法获得的定位精度更高.

Novel infrared landmark indoor positioning method based on improved IMM-UKF

In structured environment, according to the requirement of indoor robot navigation for accuracy and real-time performance, On the basis of a novel positioning method using infrared landmarks, another novel infrared landmark indoor positioning method which uses high power infrared tube as landmarks, and infrared camera as receiving sensor combined track deduction is proposed in this paper. An improved Interacting Multiple Models Unscented Kalman Filter(IMM-UKF) data fusion algorithm for the two positioning scheme is used to improve the precision. Experimental results show that compared with common positioning methods the novel infrared landmark indoor positioning method has higher speed of location and higher precision and the improved IMM UKF data fusion algorithm can improve precision more than other data fusion algorithms.