arXiv cs.CV
· Papers
BWM: A Low-Cost High-Fidelity World Simulator for Robot Learning
arXiv:2607.29302v1 Announce Type: cross Abstract: Reliable robot learning requires a world simulator that can predict action consequences before execution on physical hardware, including risky and failure-prone outcomes. Existing physics simulators require substantial asset construction and calibration and still face a