BWM: A Low-Cost High-Fidelity World Simulator for Robot Learning

arXiv:2607.29302v1 Announce Type: new 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 sim-to-real gap, while video generators often lack precise control over their responses to fine-grained robot actions. In this paper, we present the Boundless World Model (BWM), an ...