基于改进粒子滤波算法的移动机器人同步定位研究

Based on the Improved Particle Filter Algorithm of Mobile Robot Simultaneous Localization Research

目前移动机器人同步定位中,通常采用前端传感器采集的信息通过转换,反馈给处理终端,但采集的信息存在外界非线性干扰,造成机器人同步定位不准;针对这一问题,引入了一种改进粒子群滤波算法思想,利用机器人前端传感器采集的模拟量输入数据以及上位机显示的转换数据代入到改进的粒子群滤波定位模型中,保证定位精度,机器人的环境区域为150m×200m,具有20个可以检测到的环境特征,机器人在该区域中共进行了3000m的行驶测量;实验结果表明：该方法不定位精度比传统算法提高了24.3%,而且显著降低了执行时间5~9s,适于推广。

In current mobile robot simultaneous localization,usually adopt the front sensor through conversion,collection of information feedback to deal with the terminal,but the acquisition of information outside nonlinear disturbance,caused the robot simultaneous localization are inaccurate.In order to solve this problem,an improved particle swarm algorithm is introduced,using robot front-end analog input data from the sensor and PC according to transform data into to the improved particle swarm filtering positioning model,ensure the position precision,for the robot＇s environment area,with 20can detect environmental characteristics,the robot in the area of the communist party of China for a 3000mtraffic measurement.Experimental results show that the method is not location accuracy than traditional algorithm is improved by 24.3%,and significantly reduce the execution time 5~9s,suitable for promotion.