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Visual servo walking control for humanoids with finite-time convergence and smooth robot velocities

机译:具有限时收敛和平滑机器人速度的类人机器人视觉伺服行走控制

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摘要

In this paper, we address the problem of humanoid locomotion guided from information of a monocular camera. The goal of the robot is to reach a desired location defined in terms of a target image, i.e., a positioning task. The proposed approach allows us to introduce a desired time to complete the positioning task, which is advantageous in contrast to the classical exponential convergence. In particular, finite-time convergence is achieved while generating smooth robot velocities and considering the omnidirectional waking capability of the robot. In addition, we propose a hierarchical task-based control scheme, which can simultaneously handle the visual positioning and the obstacle avoidance tasks without affecting the desired time of convergence. The controller is able to activate or inactivate the obstacle avoidance task without generating discontinuous velocity references while the humanoid is walking. Stability of the closed loop for the two task-based control is demonstrated theoretically even during the transitions between the tasks. The proposed approach is generic in the sense that different visual control schemes are supported. We evaluate a homography-based visual servoing for position-based and image-based modalities, as well as for eye-in-hand and eye-to-hand configurations. The experimental evaluation is performed with the humanoid robot NAO.
机译:在本文中,我们解决了由单眼相机信息引导的人形运动问题。机器人的目标是到达根据目标图像定义的期望位置,即定位任务。所提出的方法允许我们引入期望的时间来完成定位任务,这与经典的指数收敛法相比是有利的。特别是,在生成平滑的机器人速度并考虑机器人的全向唤醒能力的同时,实现了有限时间收敛。另外,我们提出了一种基于任务的分层控制方案,该方案可以同时处理视觉定位和避障任务,而不会影响所需的收敛时间。控制器能够在人形机器人行走时激活或禁用避障任务,而无需生成不连续的速度参考。理论上,即使在任务之间的过渡期间,也证明了两个基于任务的控制的闭环的稳定性。在支持不同的视觉控制方案的意义上,所提出的方法是通用的。我们评估基于单应性的视觉伺服,以用于基于位置和基于图像的模态,以及用于手眼和手眼配置。用人形机器人NAO进行实验评估。

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