一种智能空间辅助的家庭服务机器人SLAM方法

An approach for intelligent space aided home service robot SLAM

在单机器人SLAM过程中,定位误差和建图误差随机器人运动距离增大而增大。为了有效降低SLAM误差,本文提出了一种智能空间辅助的家庭服务机器人SLAM方法。基于Rao-Blackwellized粒子滤波思想,机器人定位和建图问题被分解为两个独立环节,首先,联合机器人控制量和智能空间摄像机网络的观测值估计机器人位姿,给出了位姿粒子的采样提议分布和权值更新公式;然后,机器人利用自身位姿及对目标的观测来构建环境地图。仿真实验表明本方法有效提高了机器人的定位精度,进而得到了更加精确的环境地图。

During the process of single-robot SLAM,the localization error and mapping error increase with the robot movement distance.In this paper a novel intelligent space aided home service robot SLAM is presented.The SLAM is broken down into two separate sections on the basis of Rao-Blackwellized particle filtering theory.At first the pose of robot is estimated by combining the control variables from robot and observation values from camera network of intelligent space,and the proposal distribution for sam-pling robot pose particle and formula for updating particle weight are given.Then,the environmental map is built according to robot poses and its observations.The simulated experiments show that the proposed method could obviously improve the precision of robot localization,and get more accurate mapping result.