WebFeb 25, 2024 · A search (mapping) algorithm that takes in real-world observation and maps them to the policy-equivalent images in the simulated environment using a convolution neural network (CNN) model is proposed that can achieve high sim–real generalization at significantly low training costs. PDF View 2 excerpts, cites background WebOct 23, 2024 · 2024. TLDR. This work proposes using progressive networks to bridge the reality gap and transfer learned policies from simulation to the real world, and presents an early demonstration of this approach with a number of experiments in the domain of robot manipulation that focus on bridging thereality gap. 457. PDF.
Sim-to-Real Transfer with Neural-Augmented Robot Simulation
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