Studies in robot teleoperation have been centered around action specifications -- from continuous joint control to discrete end-effector pose control. However, these robot-centric interfaces often require skilled operators with extensive robotics expertise. To make teleoperation accessible to non-expert users, we propose the framework "Scene Editing as Teleoperation" (SEaT), where the key idea is to transform the traditional "robot-centric" interface into a "scene-centric" interface -- instead of controlling the robot, users focus on specifying the task's goal by manipulating digital twins of the real-world objects. As a result, a user can perform teleoperation without any expert knowledge of the robot hardware. To achieve this goal, we utilize a category-agnostic scene-completion algorithm that translates the real-world workspace (with unknown objects) into a manipulable virtual scene representation and an action-snapping algorithm that refines the user input before generating the robot's action plan. To train the algorithms, we procedurally generated a large-scale, diverse kit-assembly dataset that contains object-kit pairs that mimic real-world object-kitting tasks. Our experiments in simulation and on a real-world system demonstrate that our framework improves both the efficiency and success rate for 6DoF kit-assembly tasks. A user study demonstrates that SEaT framework participants achieve a higher task success rate and report a lower subjective workload compared to an alternative robot-centric interface. Video can be found at https://www.youtube.com/watch?v=-NdR3mkPbQQ .
翻译:机器人远程操作的研究围绕行动规格 -- -- 从连续的联合控制到离散的终端效应控制。 然而, 这些机器人中心界面往往需要技术熟练的操作者, 拥有广泛的机器人技术专长。 为了让非专家用户能够使用远程操作, 我们提议了一个框架“ Scene Ediction as TeleAgency” (SEAT), 关键的想法是将传统的“ 机器人中心” 界面转换成一个“ 监视中心” 界面, 而不是控制机器人, 用户侧重于通过操纵真实世界天体的数码双胞胎来指定任务。 结果, 用户可以在不拥有任何机器人硬件专家知识的情况下进行远程操作。 为了实现这一目标, 我们使用一个分类的“ 敏感化的场景完成算法”, 将真实世界的工作空间( 有未知对象) 转换成一个可manipult 虚拟场景代表器, 以及一个在生成机器人行动计划之前精细化用户输入的动作算法。 培训算法, 我们程序上生成了一个大尺度、 多样化的套装式的数据集 。 在机器人硬件硬件硬件硬件硬件硬件硬件硬件硬件中, 可以进行一个目标- kevloadal- keval- keal lade lax laud laud lax a lax a lax a laus- subild subild subild subild subild subild lad subil