未知环境下移动机器人实时路径规划

针对在未知环境下实现移动机器人实时的路径规划问题，提出了一种将快速扩展随机树（RRT）算法与视野域自适应的滚动窗口相结合的路径规划算法。该方法实时获取滚动窗口内的局部环境信息，根据环境的变化，滚动窗口视野域进行自适应调整，通过分析滚动窗口内传感器获取的信息，结合改进后的RRT算法筛选出可行的路径，控制移动机器人到达子目标点，在此过程中动态监测规划好的路径，确保路径合理，并重复上述过程，直至到达目标区域。实验对比分析表明，该方法能实时并有效实现未知环境下移动机器人的路径规划。

Real time path planning for mobile robot in unknown environment

In order to solve the problem of real-time path planning for mobile robot in unknown environment, a path planning algorithm combining Rapidly-exploring Random Tree（RRT） algorithm with visual field adaptive rolling window is proposed. The method obtains local environment information in the scroll window in real time, according to the environmental change, adjusts the rolling window view, analyzing the information obtained by sensor in the scroll window, combined with the improved RRT algorithm to screen out the feasible path, controls the mobile robot arrive at the sub target point. In this process, the path is dynamically monitored to ensure a reasonable path, and repeat this process until it reaches the target area. Experiments show that the proposed method can realize real-time path planning for mobile robots effectively in unknown environments.