基于典型栅格地图的代价地图改进方法

针对具有多种路况的复杂环境，提出了一种基于栅格地图的代价地图构建方法。改进方法分别从移动机器人可通过安全性和可通过消耗性2方面对普通的布尔栅格地图进行改进。首先，建立以机器人与障碍物距离为变量的递减代价函数和以不同路况能耗占比为变量的代价函数；然后，根据2种代价函数确定每个栅格的代价值；最后，将生成的2种代价地图融合，得到改进地图。以A*算法为例，修改其估值函数以适应新的地图，通过仿真实验对比传统地图和改进地图下的路径规划情况。实验结果表明，相对于传统的栅格地图，改进地图下规划出的路径始终保持着距离障碍物的安全距离，并且对不同价值的道路进行了选择与规避，有效地保证了移动机器人在运动过程中的安全性，并且根据实际情况考虑了能耗代价改变了路径选择，实现了多路况复杂环境下的路径规划，验证了地图改进方法的可行性。

Cost Map Improvement Method Based on Typical Grid Map

A complex map based on grid map was proposed for complex environments with multiple road conditions. The improved method improves the ordinary Boolean grid map from the mobile robot through security and consumability. Firstly, the decreasing cost function was established which is based on the distance between the robot and the obstacle; the cost function with the energy consumption ratio of different road conditions was also established.Then, the cost value of each grid was determined according to two cost functions;Finally, the two cost maps generated were merged to obtain an improved map . Taking the A* algorithm as an example, its evaluation function was modified to adapt to the new map, simulation experiments were conducted to compare the path planning situation under the traditional map and the improved map. The experimental results show that compared with the traditional grid map, the path under the improved map always maintains the safe distance from the obstacles, and the roads of different values were selected and evaded, which effectively guarantees the safety of the mobile robot during the movement process, and changes the path selection according to the actual situation, and realizes the path planning in the multi-path complex environment, which verifies the feasibility of the map improvement method.