移动机器人多信标SLAM技术

(西安科技大学 电气与控制工程学院,陕西 西安 710054)

露天移动机器人; 同时制图与定位; 导航定位; 随机信标

SLAM navigation of mobilerobots based on multi-beacons
GAO Pei-lin,GAO Yun

(College of Electrical and Control Engineering,Xi'an University of Science and Technology,Xi'an 710054,China)

mobile robots in the open air; SLAM; navigation; random beacon

备注

针对大型煤矿中的露天移动机器人自主行走问题,应用基于卡尔曼滤波的SLAM算法,研究了移动机器在不携带惯性导航设备,也无先验地图的情况下,通过自身携带的传感器与环境特征量进行应答式通信,建立环境地图,并利用该地图计算自身位置,从而实现自主导航与定位。仿真结果显示,SLAM算法的定位误差保持在±1 m以内,速度误差保持在±0.2 m/s以内,对环境特征量的定位误差随着机器人的移动逐渐减小,最终保持在±2 m以内。同时,通过对不同距离量测噪声与速度量测噪声的情况也进行了分析。仿真结果显示,当保持距离量测噪声不变,增大速度量测噪声时,或保持速度量测噪声不变,增大距离量测噪声时,SLAM算法的定位精度均会下降。研究表明,基于卡尔曼滤波的SLAM算法很好地控制了移动机器人在未知环境中的定位误差,保证了机器人的定位精度。

This article aims at the problem of autonomous walking of outdoor mobile robots in large coal mines.It focuses on a situation that a robot,which doesn't carry any inertial navigation equipment or without a priori map,communicates with the beacons,establishes the environmental maps,which is used to calculate its own position.The simulation results show that the positioning error of SLAM algorithm is keep within±1 m,the velocity error is kept within ±0.2 m/s,the beacon positioning error is decreasing while the robot is moving,and eventually kept within ±2 m.The study also finds out that distance measurement noise or velocity measurement noise will directly affect the position accuracy of SLAM algorithm.Therefore,the influence of different measurement noises is also analyzed.The accuracy of SLAM algorithm is decrease while the distance measurement noise is increased or the velocity measurement noise isincreased.The simulation results show that the SLAM algorithm based on Kalman Filtering controls the position error of mobile robot in the unknown environment well and improves the positioning accuracy of the robot effectively.