ForceTwin
“ForceTwin achieved 87.3% goal completion across nine object-embodiment pairs, versus 59.7% for VLM-prior twins and 56.9% for kinematics-only twins”
Source→“A human with a force-sensing handheld gripper can measure an object's true dynamics in minutes, producing a digital twin that nearly doubles robot manipulation success”
Source→“we replace that randomization with the identified dynamics, leaving the policy architecture and training procedure unchanged”
Source→“the wood-door policy 'succeeds on the wood door in all five trials'”
Source→“kinematics-only twins (pure feedback) had the worst tracking errors on most objects — e.g., 91.9% tracking RMSE on the oven with Spot vs. 33.3% for ForceTwin”
Source→“81.2% completion vs. 1.6% (VLM prior) and 1.5% (kinematics-only) on the metal door”
Source→“Tool trajectories come from 'Project Aria MPS' (Section IV-A)”
Source→“Ground-truth articulation axes were annotated in 'a Leica RTC360 laser scan'”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.