Title: The Pitfalls of Excessive Sim2Real Alignment: Hindering Policy Learning and Proposed Remedies

Abstract: Although sim2real strategies are essential for successfully transferring policies to physical hardware, there is a point where such efforts become counterproductive. This paper argues that the current emphasis on sim2real has created misaligned incentives with policy learning, leading to simulator lock-in and suboptimal policy exploration caused by overly restrictive real-world constraints. We provide an analysis of the root causes behind these issues and introduce a novel sim2sim2real framework as a potential solution, which utilizes the robot’s kinematics as the only design constraint.

Source: arXiv Generated at: 2026-06-03 00:00:00 UTC