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Extended tau theory for robot motion control

机译:扩展tau理论用于机器人运动控制

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Biologists proposed the tau theory to explain how animals control their motion using visual feedback for different tasks including landing and perching. Tau theory is based on a concept called time-to-contact, which is the required time to contact an object if the current velocity is maintained. Recently, tau theory has been applied to control robots' motion for similar tasks such as perching, docking, braking, or landing. However, existing tau theory can only work for the case with zero contact velocity. Some tasks such as perching actually require a non-zero contact velocity to make gripping mechanisms work. To address this problem, we extend the tau theory by proposing a two-stage strategy in one dimensional space to generate the reference trajectory for time-to-contact. Moreover, we propose a new coupling strategy to deal with the motion in three dimensional space. Simulation results demonstrate the effectiveness of proposed two-stage and coupling strategies. Moreover, we leverage a featureless method to estimate the time-to-contact from image sequences and implement it on a mobile robot platform. Experimental results also demonstrate that the non-zero contact velocity can be accomplished using onboard vision feedback. The research presented in this paper can be readily applied to control the motion of flying robots for perching with visual feedback.
机译:生物学家提出了tau理论来解释动物如何通过视觉反馈来控制着陆和栖息等不同任务的运动。 Tau理论基于称为接触时间的概念,如果保持当前速度,接触时间就是接触物体所需的时间。最近,tau理论已被用于控制机器人的运动,以完成类似的任务,例如栖息,对接,制动或着陆。但是,现有的tau理论仅适用于接触速度为零的情况。诸如栖息之类的某些任务实际上需要非零的接触速度才能使抓取机制发挥作用。为了解决这个问题,我们通过在一维空间中提出两阶段策略以生成接触时间的参考轨迹来扩展tau理论。此外,我们提出了一种新的耦合策略来处理三维空间中的运动。仿真结果证明了提出的两阶段耦合策略的有效性。此外,我们利用一种无特征的方法来估计图像序列的接触时间,并将其实现在移动机器人平台上。实验结果还表明,使用车载视觉反馈可以实现非零接触速度。本文提出的研究可以很容易地应用于控制飞行机器人的运动,并通过视觉反馈进行栖息。

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