Title: Predicted Trajectory Guidance Control Framework of Teleoperated Ground Vehicles Compensating for Delays Show Chinese title

Title: 预测轨迹引导控制框架用于补偿延迟的远控地面车辆

Abstract: Maneuverability and drivability of the teleoperated ground vehicle could be seriously degraded by large communication delays if the delays are not properly compensated. This paper proposes a predicted trajectory guidance control (PTGC) framework to compensate for such delays, thereby improving the performance of the teleoperation system. The novelty of this PTGC framework is that teleoperators intended trajectory is predicted at the vehicle side with their delayed historical control commands and the LiDAR 3D point cloud of the environment, and then the vehicle is guided by the predicted trajectory. By removing the teleoperator from the direct control loop, the presented method is less sensitive to delays, and delays are compensated as long as the prediction horizon exceeds the delays. Human-in-the-loop simulation experiments are designed to evaluate the teleoperation performance with the proposed method under five delay levels. Based on the repeated measurement analysis of variance, it is concluded that the PTGC method can significantly improve the performance of the teleoperated ground vehicles under large delays(>200ms), such as the task completion time (TCT), deviation to centerline (D2C) and steering effort (SE). In addition, the results also show that teleoperators can adapt to smaller delays, and the presented method is ineffective in such cases. Show Chinese abstract

Abstract: 如果通信延迟没有得到适当补偿，遥控地面车辆的机动性和可驾驶性可能会受到严重影响。 本文提出了一种预测轨迹引导控制（PTGC）框架来补偿此类延迟，从而提高遥操作系统的性能。 该PTGC框架的新颖之处在于，在车辆端利用操作员的历史延迟控制命令和环境的LiDAR三维点云预测操作员预期的轨迹，然后根据预测的轨迹引导车辆。 通过将操作员从直接控制回路中移除，所提出的方法对延迟的敏感性较低，并且只要预测时长超过延迟时间，就可以对其进行补偿。 设计了基于人-在-回路的仿真实验，以评估在五种不同延迟水平下使用该方法的遥操作性能。 基于重复测量方差分析的结果表明，PTGC方法可以在大延迟（>200毫秒）情况下显著改善遥控地面车辆的性能，例如任务完成时间（TCT）、偏离中心线距离（D2C）以及转向力（SE）。 此外，结果还显示操作员可以适应较小的延迟，而在这种情况下，所提出的方法无效。