论文标题

车辆遥控:连续的参考档次跟踪

Vehicle Teleoperation: Successive Reference-Pose Tracking

论文作者

Prakash, Jai, Vignati, Michele, Sabbioni, Edoardo, Cheli, Federico

论文摘要

在许多领域中,车辆遥控是一个有趣的功能。近距离操作的一个典型问题是通信时间延迟,加上执行器饱和和环境干扰,可能会导致车辆与人类操作员施加的目标轨迹的偏差,后者向车辆强加了方向盘角度参考和速度/加速度参考。通过预测技术,可以在足够的程度上考虑时间延迟。但是,在存在干扰的情况下,由于没有瞬时触觉和视觉反馈,向车辆传递的人类操纵转向命令没有车辆观察到的干扰。为了改善参考跟踪而不会在驾驶控制方面失去及时的及时性,可以将连续参考姿势的形式的参考轨迹传输,而不是转向命令到车辆。我们介绍了这个新概念,即“连续的参考档次跟踪(SRPT)”,以改善车辆近路的路径跟踪。本文讨论了这种新方法的可行性和优势,与史密斯预测器控制方法相比。模拟是在Simulink环境中进行的,在该环境中,在存在可变网络延迟的情况下,通过Smith和SRPT控制器控制了14DOF车辆模型。性能比较的场景是低粘附地面,强烈的侧向风和驾驶速度要求操作。模拟结果显示,使用SRPT方法进行参考跟踪的显着改善。

Vehicle teleoperation is an interesting feature in many fields. A typical problem of teleoperation is communication time delay which, together with actuator saturation and environmental disturbance, can cause a vehicle deviation from the target trajectory imposed by the human operator who imposes to the vehicle a steering wheel angle reference and a speed/acceleration reference. With predictive techniques, time-delay can be accounted at sufficient extent. But, in presence of disturbances, due to the absence of instantaneous haptic and visual feedback, human-operator steering command transmitted to the the vehicle is unaccounted with disturbances observed by the vehicle. To improve reference tracking without losing promptness in driving control, reference trajectory in the form of successive reference poses can be transmitted instead of steering commands to the vehicle. We introduce this new concept, namely, the 'successive reference-pose tracking (SRPT)' to improve path tracking in vehicle teleoperation. This paper discusses feasibility and advantages of this new method, compare to the smith predictor control approach. Simulations are performed in SIMULINK environment, where a 14-dof vehicle model is being controlled with Smith and SRPT controllers in presence of variable network delay. Scenarios for performance comparison are low adhesion ground, strong lateral wind and steer-rate demanding maneuvers. Simulation result shows significant improvement in reference tracking with SRPT approach.

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