应用于地面无人车辆的窗口约束马尔可夫定位

Window Constrained Markov Localization for Unmanned Ground Vehicle

为解决地面无人车辆在GPS易受干扰区域的定位问题,提出一种窗口约束马尔可夫定位方法,通过在窗口范围内进行马尔可夫定位减少更新的状态空间范围.窗口的位置在初始时刻参考地图中建立的路标估计,并随车辆运动信息在地图中移动.该方法能够减少定位过程中的计算量,除初始时刻外不依赖于GPS进行短期外推定位,且实验证明具有较好的实时性和准确性.

To solve the localization problem of unmanned ground vehicle when the signals of GPS are susceptible to be disturbed,a window constrained Markov localization method was proposed. The scope of state space was constrained when Markov localization was taken within the window. The window＇s position can be determined initially refer to landmarks built in the map, and moved with vehicle＇s movement. This method can reduce the amount of calculation and does not rely on satellite positioning system besides initial time. The positioning accuracy and real-time performance are testified on a full-sized unmanned ground vehicle.