Fig. 6: F-TAC Hand’s adaptive behaviours.
From: Embedding high-resolution touch across robotic hands enables adaptive human-like grasping
a, F-TAC Hand’s ability to grasp multiple objects simultaneously in a human-like manner. b, Despite execution noise, F-TAC Hand can optimize object transport through multi-object grasping. c, Real-world disturbances significantly increase second-grasp collision rates (inset: collision detection point in red), highlighting the necessity of tactile monitoring. d, Tactile-informed adaptation significantly improves second-grasp success rates. Plots c and d show 60 independent technical replicates (blue dots), each representing a unique object combination tested across 10 trials. Box plots show 25th–75th percentiles (box), median (centre line) and minimum/maximum values (whiskers). Shaded areas (orange in c, green in d) show kernel-density estimations of data distribution. The identical P values (2.1 × 10−17) displayed in the two panels derive from one-sided paired t-tests (t(59) = 11.8) comparing perfect versus real-world execution (c) and with versus without tactile-informed adaptation (d). No adjustments were made for multiple comparisons.
