论文标题
对自动机器人车辆的控制策略的审查:理论,模拟和实验
A review of path following control strategies for autonomous robotic vehicles: theory, simulations, and experiments
论文作者
论文摘要
本文对自动机器人车的路径主题进行了深入的评论,并在二维空间(2D)中特别关注车辆运动。从控制系统的角度来看,可以将以下路径提出为稳定路径以下误差系统的问题,该系统描述了相对于路径的车辆的位置动力和可能的方向错误,并且在适当的参考框架中定义了错误。尽管文献中描述的方法有多种路径,但我们表明,原则上,大多数可以分为两组:稳定路径以下误差系统在车辆的车身框架中或连接到“参考点”沿路径的框架中表示,例如沿路径的“参考点”,例如frenet-serret(f-s-serret(f-s)框架(f-s)框架或平行传输(p-p t)。通过这种观察,我们提供了一种简单但概括的统一配方,以涵盖文献中可用的许多方法。然后,我们从设计和实现的角度进行比较,讨论每种方法的优点和缺点。我们进一步显示了从野外试验测试获得的路径的实验结果,该方法通过射入不足和完全驱动的自动驾驶汽车进行了测试。此外,我们引入了开源MATLAB和凉亭/ROS仿真工具箱,这些工具箱有助于测试方法之后的方法,然后将其集成到自动驾驶汽车的组合指导,导航和控制系统中。
This article presents an in-depth review of the topic of path following for autonomous robotic vehicles, with a specific focus on vehicle motion in two dimensional space (2D). From a control system standpoint, path following can be formulated as the problem of stabilizing a path following error system that describes the dynamics of position and possibly orientation errors of a vehicle with respect to a path, with the errors defined in an appropriate reference frame. In spite of the large variety of path following methods described in the literature we show that, in principle, most of them can be categorized in two groups: stabilization of the path following error system expressed either in the vehicle's body frame or in a frame attached to a "reference point" moving along the path, such as a Frenet-Serret (F-S) frame or a Parallel Transport (P-T) frame. With this observation, we provide a unified formulation that is simple but general enough to cover many methods available in the literature. We then discuss the advantages and disadvantages of each method, comparing them from the design and implementation standpoint. We further show experimental results of the path following methods obtained from field trials testing with under-actuated and fully-actuated autonomous marine vehicles. In addition, we introduce open-source Matlab and Gazebo/ROS simulation toolboxes that are helpful in testing path following methods prior to their integration in the combined guidance, navigation, and control systems of autonomous vehicles.