RAFL: Generalizable Sim-to-Real of Soft Robots with Residual Acceleration Field Learning
RAFL: Generalizable Sim-to-Real of Soft Robots with Residual Acceleration Field Learning explores A framework that improves the accuracy of soft robot simulations across different shapes by learning a transferable corrective dynamics field.. Commercial viability score: 4/10 in Robotics Simulation.
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