In immersive humanoid robot teleoperation, there are three main shortcomings that can alter the transparency of the visual feedback: 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 drawbacks, 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 the effectiveness of our solution.
翻译:在暗淡的人类机器人远程操作中,有三个主要缺陷可以改变视觉反馈的透明度:操作员和机器人头部运动之间的延迟,原因是网络通信延迟或机器人联合动作缓慢。这种延迟可能导致视觉反馈出现明显延迟,从而危及变形质量,可能造成晕眩,影响互动,导致操作员经常运动暂停视觉反馈,从而导致操作员为视觉反馈解决而进行静默;(二)相机和头盔外视场(FOV)之间的不匹配,前者一般为低视野;以及(三)由于人和机器人头部运动范围之间的不匹配,后者一般也比较低。为了利用这些退步,我们为人类的视觉反馈开发了一种分解式的观点控制解决方案,使摄像机的视觉反馈能够低延缓,人为地增加机的视野范围,与操作员头部相匹配。我们的新解决方案使用SLM技术从重建的图像组合点上加强视觉反馈,以真实的图像控制方向为基础,在图像操作员的视觉反馈中进行真正的图像定位,而机头部的图像分析结果则由真正的机器人组成。