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PREDICTION ON TOP-DOWN SCENES BASED ON OBJECT MOTION

机译:基于对象运动的自上而下场景预测

摘要

Techniques for determining predictions on a top-down representation of an environment based on object movement are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) may capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle, a pedestrian, a bicycle). A multi-channel image representing a top-down view of the object(s) and the environment may be generated based in part on the sensor data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) may also be encoded in the image. Multiple images may be generated representing the environment over time and input into a prediction system configured to output a trajectory template (e.g., general intent for future movement) and a predicted trajectory (e.g., more accurate predicted movement) associated with each object. The prediction system may include a machine learned model configured to output the trajectory template(s) and the predicted trajector(ies).
机译:这里讨论了基于对象运动的基于对象移动的环境的自上而下表示的预测的技术。第一车辆(例如自主车辆)的传感器可以捕获环境的传感器数据,该环境可以包括与第一车辆分开的对象(例如。,车辆,行人,一个行人自行车)。可以基于传感器数据基于部分地基于传感器数据生成代表对象的自上视图和环境的多通道图像。环境数据(物体范围,速度,车道位置,人行横道,等)也可以在图像中编码。可以生成多个图像随时间表示环境,并输入被配置为输出轨迹模板的预测系统(例如。,未来运动的一般意图)和预测的轨迹(例如。,更准确的预测运动)与每个对象相关联。预测系统可以包括机器学习模型,其被配置为输出轨迹模板和预测的轨迹(IE)。

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