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Suboptimal immediate navigational response based on long term planning

机译:基于长期计划的次优即时导航响应

摘要

Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques. In one implementation, a navigation system for a host vehicle may include at least one processing device programmed to: receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify a navigational state associated with the host vehicle; provide the navigational state to a trained navigational system; receive, from the trained navigational system, a desired navigational action for execution by the host vehicle in response to the identified navigational state; analyze the desired navigational action relative to one or more predefined navigational constraints; determine an actual navigational action for the host vehicle, wherein the actual navigational action includes at least one modification of the desired navigational action determined based on the one or more predefined navigational constraints; and cause at least one adjustment of a navigational actuator of the host vehicle in response to the determined actual navigational action for the host vehicle.
机译:提供了用于使用强化学习技术来导航自动驾驶车辆的系统和方法。在一种实施方式中,用于本车的导航系统可以包括至少一个处理装置,该处理装置被编程为:从照相机接收代表本车​​的环境的多个图像;分析多个图像以识别与本车辆相关联的导航状态;向训练有素的导航系统提供导航状态;从经训练的导航系统接收期望的导航动作,以响应于识别出的导航状态由本车辆执行;分析相对于一个或多个预定义的导航约束的期望的导航动作;确定主车辆的实际导航动作,其中,实际导航动作包括基于一个或多个预定义的导航约束确定的期望的导航动作的至少一种修改;并响应于为宿主车辆确定的实际导航动作,引起宿主车辆的导航致动器的至少一种调整。

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