Uncertainty-Aware Finger Force Estimation for Reliable Box Manipulation
With force adaptation
FEEL힘 적응을 적용한 실제 로봇 영상
추정한 힘에 따라 손가락이 닫히고 멈추거나 열리는 장면
배경에 실제 실험에 사용한 박스들이 보이도록
Without force adaptation
Baseline힘 적응 없이 수행한 실제 로봇 영상
고정된 손가락 명령으로 같은 작업을 수행한 장면
위 영상과 같은 시점으로 비교할 수 있도록
10 trials per condition, using the same box specification and predefined motion. Reliability = successful placement without recorded damage.
Applied to all experiment grids below.
Success indicates task completion without recorded damage. Failure indicates an incomplete task or recorded damage.
With force estimation experiments
(Kp, Kd) = (200, 400)Force-adaptive manipulation driven by FEEL estimates.
Without force estimation experiments
(Kp, Kd) = (200, 400)Fixed finger commands without force-estimation feedback.
Gain comparison experiments
Ten force-adaptive box-manipulation trials for each controller-gain setting.
(Kp, Kd) = (100, 200)
RMSE: 0.233 ± 0.005 N
(Kp, Kd) = (200, 400)
Used in the main experimentsRMSE: 0.251 ± 0.010 N
(Kp, Kd) = (300, 600)
RMSE: 0.255 ± 0.008 N
Data collection
Wearable F/T reference measurements synchronized with per-finger proprioceptive histories.
Approximately 25,000 synchronized estimator samples were collected per finger. Robot states and F/T measurements were aligned by timestamp.
Uncertainty-aware force estimation
Per-finger force estimates and predictive uncertainty under proprioceptive ambiguity.
불확실성 기반 힘 추정 영상
손가락별 추정 힘과 예측 불확실성이 함께 보이도록