Proactive Grasp Assistance in a Robotic Hand Exoskeleton Improves Performance and Preference in Challenging Tasks
Benjamin Davis, Emily Huynh, Hannah S. Stuart
AI summary
Problem
It remains unclear how proactive robotic assistance affects the user's sense of agency and experience in wearable grasping devices, where physical coupling could disrupt control.
Approach
We evaluated a two-finger hand exoskeleton where users navigated a virtual task under varying difficulties, comparing unassisted, timid, and aggressive proactive assistance modes while measuring performance, interaction forces, and user surveys.
Key results
- Aggressive assistance significantly improved success rates in difficult tasks
- Users strongly preferred proactive assistance during challenging trials
- Proactive assistance preserved the user's sense of agency
- Interaction forces effectively tracked user-robot dynamics
Why it matters
Findings guide the design of wearable assistive robots by showing that proactive help can enhance performance and acceptance without sacrificing user control.
Abstract
Advancements in perception, planning, and con- trol enable the development of wearable robots capable of proactively assisting users in avoiding potentially negative outcomes. However, the introduction of robotic assistance in general is often associated with a loss in the sense of agency, a factor traditionally associated with overall device acceptance. Recent work provides a different perspective, showing that contextual proactive assistance is well-received for teleoperation or shared workspace tasks. Still, no works have investigated the impact of proactive assistance for wearable grasping devices, where physical interactions have increased potential for dis- rupting the user’s experience. In this study, we analyze the impact of proactive assistance in a hand exoskeleton with an abstracted grasping task of varying difficulty. We show that in general, the presence of assistance does not significantly reduce experience or the sense of agency. In fact, in a difficult task, subjects strongly prefer proactive assistance, likely as a result of its provided utility. When the task is easily completed without assistance, subjects indicate no strong preference for assisted conditions. Our results challenge the notion of a direct trade-off between robotic assistance and agency, suggesting that well-designed assistance can improve performance and user preference without compromising their sense of control.