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首页> 外文会议>Conference on sensor fusion and decentralized control in robotic system >Automatic Lane Keeping of a Vehicle Based on Perception Net
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Automatic Lane Keeping of a Vehicle Based on Perception Net

机译：基于感知网的车辆自动行车道

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The objective of this research is to monitor and control the vehicle motion in order to remove out the existing safety risk based upon the human-machine cooperative control. A predictive control method is proposed to control the steering wheel of the vehicle to keep the lane. Desired angle of the steering wheel to control the vehicle motion could be calculated based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net, where not only the state variables, but also the corresponding uncertainties were propagated in forward and backward direction in such a way to satisfy the given constraint condition, maintain consistency, reduce the uncertainties, and guarantee robustness. A series of experiments was conducted to evaluate the control performance, in which a car like robot was utilized to quit unwanted safety problem. As the results, the robot was keeping very well a given lane with arbitrary shape at moderate speed.
机译：该研究的目的是监测和控制车辆运动，以基于人机协作控制来消除现有的安全风险。提出了一种预测控制方法来控制车辆的方向盘以保持车道。可以基于车辆动力学，电流和估计的车辆的每个样品步骤来计算用于控制车辆运动的方向盘的所需角度。通过从相机图像，转速计和方向盘编码器的几何定影传感器数据，虽然感知网，但是，在不仅状态变量，而且相应的不确定性也在这样的情况下，通过几何定影传感器数据来计算车辆姿势和道路曲率。满足给定的约束条件的方法，保持一致性，降低不确定性，并保证鲁棒性。进行了一系列实验以评估控制性能，其中利用机器人避免不需要的安全问题。结果，机器人保持非常好的给定车道，其具有中等速度的任意形状。

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