Upper-limb amputees face tremendous difficulty in operating dexterous powered prostheses. Previous work has shown that aspects of prosthetic hand, wrist, or elbow control can be improved through "intelligent" control, by combining movement-based or gaze-based intent estimation with low-level robotic autonomy. However, no such solutions exist for whole-arm control. Moreover, hardware platforms for advanced prosthetic control are expensive, and existing simulation platforms are not well-designed for integration with robotics software frameworks. We present the Prosthetic Arm Control Testbed (ProACT), a platform for evaluating intelligent control methods for prosthetic arms in an immersive (Augmented Reality) simulation setting. We demonstrate the use of ProACT through preliminary studies, with non-amputee participants performing an adapted Box-and-Blocks task with and without intent estimation. We further discuss how our observations may inform the design of prosthesis control methods, as well as the design of future studies using the platform. To the best of our knowledge, this constitutes the first study of semi-autonomous control for complex whole-arm prostheses, the first study including sequential task modeling in the context of wearable prosthetic arms, and the first testbed of its kind. Towards the goal of supporting future research in intelligent prosthetics, the system is built upon on existing open-source frameworks for robotics, and is available at https://arm.stanford.edu/proact.

翻译：上肢截肢者在操作灵巧的动力假肢方面面临巨大困难。先前的研究表明，通过将基于运动或注视的意图估计与底层机器人自主性相结合，采用"智能"控制可以改善假肢手、腕或肘部的控制性能。然而，目前尚不存在针对整臂控制的此类解决方案。此外，用于先进假肢控制的硬件平台成本高昂，而现有的仿真平台并未针对机器人软件框架的集成进行优化设计。我们提出了假肢手臂控制测试平台（ProACT），这是一个在沉浸式（增强现实）仿真环境中评估假肢手臂智能控制方法的平台。我们通过初步研究展示了ProACT的使用情况，非截肢参与者在使用和不使用意图估计的情况下执行了经过改编的方盒积木任务。我们进一步讨论了观察结果如何为假肢控制方法的设计以及未来使用该平台的研究设计提供参考。据我们所知，这是首次针对复杂整臂假肢的半自主控制研究，首次在可穿戴假肢背景下包含顺序任务建模的研究，也是首个此类测试平台。为支持智能假肢领域的未来研究，该系统基于现有的开源机器人框架构建，可通过 https://arm.stanford.edu/proact 获取。