基于三位置超声波检测的改进强跟踪UKF-SLAM方法研究

Research on improved strong tracking UKF-SLAM method based on three-position ultrasonic detection

针对移动机器人使用超声波传感器检测环境时存在干扰与数据不确定性问题,在分析超声波传感器工作原理和相邻位置检测数据的关联特性后,提出了基于三位置超声波检测的环境轮廓构建方法,利用超声波对室内环境进行建图;再使用改进强跟踪UKF-SLAM将超声波测量数据和移动机器人驱动模型进行滤波融合,得到更准确的位姿信息与地图特征。搭建仿真环境,并通过搭载有超声波传感器的全向轮移动机器人在实验环境内验证。仿真结果表明改进方法与其他算法相比,定位和地图构建的误差降低58.058%。室内实验中,获取环境特征的平均误差降低了50.2863%,进一步验证了提出算法的可行性与有效性。该方法对机器人同步定位与地图构建有一定参考价值。

For mobile robot using ultrasonic sensors detect interference existing in the environmental outline and the data uncertainty problems,based on the analysis of working principle of the ultrasonic sensors and the adjacent position after the correlation characteristics of detecting data,three position is proposed based on ultrasonic environmental detection method.First by using ultrasonic sensors to build the interior environment figure;Then the improved strong tracking UKF-SLAM method filters the ultrasonic measurement data and the driving model of mobile robot and gets more accurate pose information and map features after fusion optimization.In this study,setting up a simulation environment and assembling an Omni-directional mobile robot equipped with ultrasonic sensor in an indoor experimental to verify the feasibility and accuracy of algorithm.The simulation results show that the error in simultaneous localization and mapping was reduced by 58.058%that compared with the other algorithm.Furthermore,the average error of the robot’s acquisition of environmental features is reduced by 50.2863%.The feasibility and effectiveness of the improved algorithm proposed in this paper are further verified,and the method has certain reference value for Simultaneous Localization and Mapping.