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Zero-shot sim-to-real transfer of tasks with complex dynamics is a highlychallenging and unsolved problem. A number of solutions have been proposed inrecent years, but we have found that many works do not present a thoroughevaluation in the real world, or underplay the significant engineering effortand task-specific fine tuning that is required to achieve the publishedresults. In this paper, we dive deeper into the sim-to-real transfer challenge,investigate why this is such a difficult problem, and present objectiveevaluations of a number of transfer methods across a range of real-world tasks.Surprisingly, we found that a method which simply injects random forces intothe simulation performs just as well as more complex methods, such as thosewhich randomise the simulator's dynamics parameters, or adapt a policy onlineusing recurrent network architectures.

Crossing The Gap: A Deep Dive into Zero-Shot Sim-to-Real Transfer for Dynamics