Human-in-the-Loop Optimization of Shared Autonomy in Assistive Robotics
Human-in-the-Loop Optimization of Shared Autonomy in Assistive Robotics
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DOI：
10.1109/lra.2016.2593928
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发表时间：
2017-01-01
影响因子：
5.2
通讯作者：
Argall, Brenna D.
中科院分区：
文献类型：
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作者：
Gopinath, Deepak;Jain, Siddarth;Argall, Brenna D.
在本文中，我们提出了一个数学框架，将辅助机器人中用户驱动的共享自主定制形式化为非线性优化问题。我们的见解是允许最终用户而不是依赖标准优化技术来执行优化过程，从而使我们能够不确定成本函数的确切性质。我们通过交互式优化程序来奠定我们的形式主义，该程序使用辅助机械臂定制控制共享。我们还提出了一项试点研究，探索与最终用户的交互优化。这项研究涉及 17 名受试者（4 名患有脊髓损伤，13 名未受伤）。结果显示所有受试者都能够收敛到辅助范式，这表明存在最佳解决方案。值得注意的是，援助的数量并不总是针对任务绩效进行优化。相反，一些受试者倾向于在执行过程中保留更多的控制权，而不是更好的任务表现。该研究支持用户驱动的定制案例，并为其持续开发和研究提供指导。
In this paper, we propose a mathematical framework which formalizes user-driven customization of shared autonomy in assistive robotics as a nonlinear optimization problem. Our insight is to allow the end-user, rather than relying on standard optimization techniques, to perform the optimization procedure, thereby allowing us to leave the exact nature of the cost function indeterminate. We ground our formalism with an interactive optimization procedure that customizes control sharing using an assistive robotic arm. We also present a pilot study that explores interactive optimization with end-users. This study was performed with 17 subjects (4 with spinal cord injury, 13 without injury). Results show all subjects were able to converge to an assistance paradigm, suggesting the existence of optimal solutions. Notably, the amount of assistance was not always optimized for task performance. Instead, some subjects favored retaining more control during the execution over better task performance. The study supports the case for user-driven customization and provides guidance for its continued development and study.