In the project, the vehicle was first controlled with ROS. For this purpose, the necessary nodes were prepared to be controlled with a joystick. Afterwards, DWA(Dynamic Window Approach), TEB(Timed-Elastic Band) and APF(Artificial Potential Field) path planning algorithms were applied to MIT RACECAR, respectively. These algorithms have advantages and disadvantages against each other on different issues. For this reason, a scenario was created to compare algorithms. On a curved double lane road created according to this scenario, MIT RACECAR has to follow the lanes and when it encounters an obstacle, it has to change lanes without leaving the road and pass without hitting the obstacle. In addition, an image processing algorithm was developed to obtain the position information of the lanes needed to implement this scenario. This algorithm detects the target point by processing the image taken from the ZED camera and gives the target point information to the path planning algorithm. After the necessary tools were created, the algorithms were tested against the scenario. In these tests, measurements such as how many obstacles the algorithm successfully passed, how simple routes it chose, and computational costs they have. According to these results, although it was not the algorithm that successfully passed the most obstacles, APF was chosen due to its low processing load and simple working logic. It was believed that with its uncomplicated structure, APF would also provide advantages in the future stages of the project.
翻译:在该项目中,该车辆首先被ROS控制。 为此,已经准备了必要的节点,以便用操纵杆来控制。随后,DWA(动态窗口方法)、TEB(时速电子波段)和APF(人工潜能场)路径规划算法分别适用于MIT RACACAR。这些算法在不同问题上具有利弊。为此,创造了一种比较算法的假想。在这个假想中,MIT RACECAR不得不沿着一条弯曲的双行道走,当它遇到障碍时,它必须改变航道,而没有遇到障碍。此外,还开发了图像处理算法,以获得执行这一假设所需的航道位置信息。这些算法通过处理ZED相机拍摄的图像,将目标点信息提供给路径规划算法。在创造必要的工具之后,对运算法进行了测试。在这些测试中,测量了多少障碍顺利通过,如何顺利通过航道,通过航道,而没有遇到障碍。此外,它选择了最简单的航道处理方法,并且计算了这些运算法也是正常的。