Path planning and obstacle avoidance are essential for autonomous driving cars. On the base of a self-constructed smart obstacle avoidance car, which used a LeTMC-520 depth camera and Jetson controller, this paper established a map of an unknown indoor environment based on depth information via SLAM technology. The Dijkstra algorithm is used as the global path planning algorithm and the dynamic window approach (DWA) as its local path planning algorithm, which are applied to the smart car, enabling it to successfully avoid obstacles from the planned initial position and reach the designated position. The tests on the smart car prove that the system can complete the functions of environment map establishment, path planning and navigation, and obstacle avoidance.

中文翻译：

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基于Dijkstra算法和动态窗口方法的智能汽车路径规划。

路径规划和避障对于自动驾驶汽车至关重要。在使用LeTMC-520深度摄像头和Jetson控制器的自行构造的智能避障车的基础上，本文通过SLAM技术基于深度信息建立了未知室内环境的地图。Dijkstra算法用作全局路径规划算法，动态窗口方法（DWA）作为其局部路径规划算法，已应用于智能车，从而使其能够成功避开计划的初始位置的障碍物并到达指定位置。在智能汽车上的测试证明该系统可以完成环境图建立，路径规划和导航以及避障的功能。