栅格法作为目前最成熟的轨迹规划算法，由W.E.Howden于1968年

As the most mature trajectory planning algorithm, the grid method was first proposed by WEHowden in 1968 [1]. Its principle is the ability to carry out image information of the external environment. In reference to the uncertainty of sensor measurement, the literature [2] applied the idea of ​​probabilistic reasoning to the establishment of raster maps, and used different algorithms to verify that the original Bayesian inference algorithm and Dempster fusion algorithm updated the grid map in real time. The performance of moving target detection is better. Literature [3] proposes a complete traversal grid method static environment modeling for the global environment and a grid method dynamic environment modeling for the local environment while walking and measuring, and uses real-time updated information to identify the model to improve the model’s performance accuracy. Reference [4] first numbered the grid map to facilitate quick acquisition of obstacle levels

Grid method, as the most mature trajectory planning algorithm, was first proposed by W.E. Howden in 1968. In view of the uncertainty of sensor measurement, the probability reasoning thought is used for the establishment of grid map, and different algorithms are used to verify the discovery that the original Bayess reasoning algorithm and Dempster fusion algorithm perform better in updating grid map and motion target detection in real time. The paper proposes the modeling of the static environment of the full traversal raster method for the global environment and the dynamic environment modeling of the grid method for the edge-walking measurement of the local environment, and uses the information updated in real time to identify the model in order to improve the accuracy of the model. The literature first numbers the grid map to facilitate quick access to obstacle positions

Grid method, as the most mature trajectory planning algorithm, was first proposed by W.E. Howden in 1968. Its principle is the ability to carry out the image information of the external environment. In reference [2], aiming at the uncertainty of sensor measurement, probabilistic reasoning is applied to the establishment of raster map, and different algorithms are used to verify. It is found that the original Bayesian inference algorithm and Dempster fusion algorithm perform better in real-time updating raster map and moving target detection. In reference [3], the static environment modeling based on the complete ergodic grid method for the global environment and the grid method for dynamic environment modeling while walking for the local environment were proposed, and the real-time updated information was used to identify the model to improve the accuracy of the model. In reference [4], firstly, the raster map was numbered to obtain the obstacle position quickly<br>