基于SLAM的沉浸式人形机器人遥操作增强视觉反馈解耦视点控制

Yang Chen, Leyuan Sun, M. Benallegue, Rafael Cisneros, R. P. Singh, K. Kaneko, Arnaud Tanguy, Guillaume Caron, Kenji Suzuki, A. Kheddar, F. Kanehiro
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引用次数: 0

摘要

在沉浸式人形机器人遥操作中,有三个主要缺点会改变视觉反馈的透明度:(i)由于网络通信延迟或机器人关节运动缓慢,操作员和机器人头部的运动之间存在滞后。这种延迟可能导致视觉反馈的明显延迟,从而危及实施例质量,可能导致头晕,并影响交互性,导致操作员频繁的运动暂停以解决视觉反馈;(ii)相机与头戴式耳机的视场(FOV)不匹配,前者的视场通常较低;(三)人与机器人的颈部活动范围不匹配,后者也普遍较低。为了利用这些缺点,我们为人形平台开发了一种解耦的视点控制解决方案,该解决方案允许低延迟的视觉反馈,并人为地增加相机的FOV范围,以匹配操作员的耳机。我们的新解决方案使用SLAM技术来增强重建网格的视觉反馈,补充机器人视觉反馈未覆盖的区域。视觉反馈以点云的形式实时呈现给操作者。因此,通过观察点云的姿态,操作员可以从机器人的头部方向获得实时视觉。考虑到控制系统的安全性和鲁棒性,在基于虚拟现实的远程操作中,平衡这种感知和沉浸感是很重要的。实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Visual Feedback with Decoupled Viewpoint Control in Immersive Humanoid Robot Teleoperation using SLAM
In immersive humanoid robot teleoperation, there are three main shortcomings that can alter the transparency of the visual feedback: (i) the lag between the motion of the operator's and robot's head due to network communication delays or slow robot joint motion. This latency could cause a noticeable delay in the visual feedback, which jeopardizes the embodiment quality, can cause dizziness, and affects the interactivity resulting in operator frequent motion pauses for the visual feedback to settle; (ii) the mismatch between the camera's and the headset's field-of-views (FOV), the former having generally a lower FOV; and (iii) a mismatch between human's and robot's range of motions of the neck, the latter being also generally lower. In order to leverage these draw-backs, we developed a decoupled viewpoint control solution for a humanoid platform which allows visual feedback with low-latency and artificially increases the camera's FOV range to match that of the operator's headset. Our novel solution uses SLAM technology to enhance the visual feedback from a reconstructed mesh, complementing the areas that are not covered by the visual feedback from the robot. The visual feedback is presented as a point cloud in real-time to the operator. As a result, the operator is fed with real-time vision from the robot's head orientation by observing the pose of the point cloud. Balancing this kind of awareness and immersion is important in virtual reality based teleoperation, considering the safety and robustness of the control system. An experiment shows that the effectiveness of our solution.
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