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Controlling the Motions of an Autonomous Vehicle using a Local Navigator

机译:使用本地导航器控制自动驾驶汽车的运动

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This paper addresses the problem of controlling the motion of an autonomous vehicle. This research is carried out within the framework of the French INRIA/INRETS Praxitele project on public transporation by individual electric cars. In this project the cars must have the ability to perform certain motions autonomously. For that purpose we have designed a specific control architecture based upon a local navigator, which projects in the robot evolution space admissible trajectories, called escape lines, on a short time horizon using a direct model of the mobile robot. After the removal of the escape lines that cross some obstacles, it chooses the best escape line that matches with the planned path and delivers it to the inputs of the servo controllers of the vehicle. The trajectories delivered by the local navigator respect the kinematic and dynamic constraints of the vehicle (as embedded in the direct model that is used). since the local navigator only requires a proximity map obtained from sensory data rather than an exhaustive map of the vehicle's environment, its running time is low.
机译:本文解决了控制自动驾驶汽车运动的问题。这项研究是在法国INRIA / INRETS普莱西特(Praxitele)项目的框架内进行的,该项目涉及通过电动汽车进行的公共交通。在这个项目中,汽车必须具有自主执行某些运动的能力。为此,我们设计了基于本地导航器的特定控制架构,该导航器使用移动机器人的直接模型在较短的时间范围内在机器人演化空间中投影了允许的轨迹(称为逃生线)。移除越过某些障碍物的逃生线后,它会选择与计划路径相匹配的最佳逃生线,并将其传送到车辆伺服控制器的输入。本地导航器传递的轨迹遵循车辆的运动学和动态约束(嵌入在使用的直接模型中)。由于本地导航器仅需要从感官数据获得的接近图,而不是车辆环境的详尽图,因此其运行时间很短。

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