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Extended Predictive Model-Mediated Teleoperation of Mobile Robots through Multilateral Control

机译:通过多边控制扩展预测模型介导的移动机器人遥操作

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Despite the substantial progression of autonomous driving systems, their application is often limited e.g. due to safety margins which can be caused by uncertainties in the environment reconstruction. Then, via teleoperation as a fallback solution, a human-in-the-loop can be introduced as the main decision maker. However, high delay in the communication channel distorts the performance of direct force feedback teleoperation for example in space or disaster scenarios. On the other hand, model-mediated teleoperation can provide instantaneous and even predictive force feedback to the user, but the performance is limited due to state mismatches, incomplete models, model errors and the modeling challenges of complex wheel-ground contacts. Therefore, in this paper we introduce the concept of extended model-mediated teleoperation with a car like interface for mobile robots by fusing local fictitious and remote force feedback, which can be measured, computed or fictitious. We provide a method to guarantee stability of the extended model-mediated teleoperation (involving time delay, multilateral coupling, fictitious force feedback and permanent updates of the local model) based on the passivity theorem. The benefits of the approach are highlighted by human-in-the-loop experiments with a wheeled mobile robot.
机译:尽管自动驾驶系统取得了长足的进步,但是它们的应用通常受到限制,例如在自动驾驶系统中。由于环境重建不确定性可能导致的安全裕度。然后,通过远程操作作为后备解决方案,可以引入“在环人”作为主要决策者。但是,通信信道中的高延迟会扭曲直接力反馈远程操作的性能,例如在太空或灾难情况下。另一方面,模型介导的遥操作可以向用户提供瞬时甚至预测的力反馈,但是由于状态不匹配,模型不完整,模型错误以及复杂的轮-地接触的建模挑战,性能受到限制。因此,在本文中,我们通过融合可以测量,计算或虚拟的局部虚拟和远程力反馈,介绍了扩展模型介导的远程操作的概念,该模型具有用于移动机器人的类似于汽车的界面。我们提供了一种基于无源性定理的方法来确保扩展模型介导的远程操作(涉及时间延迟,多边耦合,虚拟力反馈和局部模型的永久更新)的稳定性。通过轮式移动机器人进行的在环实验,凸显了该方法的优势。

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