Shared control can ease and enhance a human operator's ability to teleoperate robots, particularly for intricate tasks demanding fine control over multiple degrees of freedom. However, the arbitration process dictating how much autonomous assistance to administer in shared control can confuse novice operators and impede their understanding of the robot's behavior. To overcome these adverse side-effects, we propose a novel formulation of shared control that enables operators to tailor the arbitration to their unique capabilities and preferences. Unlike prior approaches to customizable shared control where users could indirectly modify the latent parameters of the arbitration function by issuing a feedback command, we instead make these parameters observable and directly editable via a virtual reality (VR) interface. We present our user-customizable shared control method for a teleoperation task in SE(3), known as the buzz wire game. A user study is conducted with participants teleoperating a robotic arm in VR to complete the game. The experiment spanned two weeks per subject to investigate longitudinal trends. Our findings reveal that users allowed to interactively tune the arbitration parameters across trials generalize well to adaptations in the task, exhibiting improvements in precision and fluency over direct teleoperation and conventional shared control.

翻译：共享控制能够减轻并增强操作者遥操作机器人的能力，尤其适用于需要精细控制多自由度的复杂任务。然而，决定共享控制中自主辅助程度的仲裁过程可能令新手操作者困惑，并阻碍其对机器人行为的理解。为克服这些负面效应，我们提出了一种新颖的共享控制公式，使操作者能够根据自身能力与偏好定制仲裁策略。不同于以往可定制共享控制方法中用户通过反馈指令间接修改仲裁函数隐含参数的做法，我们使这些参数可视化，并通过虚拟现实界面直接编辑。我们针对SE(3)中的遥操作任务（即"蜂鸣线游戏"）展示了该用户可定制共享控制方法。通过用户实验，让参与者通过虚拟现实操控机械臂完成游戏，每个受试者实验周期持续两周以研究纵向趋势。研究结果表明，允许用户在试验间交互式调整仲裁参数的方案能够良好适应任务变化，在精度与流畅性方面均优于直接遥操作及传统共享控制方法。