arXiv Open Access 2024

Sim-to-Real gap in RL: Use Case with TIAGo and Isaac Sim/Gym

Jaume Albardaner Alberto San Miguel Néstor García Magí Dalmau-Moreno

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This paper explores policy-learning approaches in the context of sim-to-real transfer for robotic manipulation using a TIAGo mobile manipulator, focusing on two state-of-art simulators, Isaac Gym and Isaac Sim, both developed by Nvidia. Control architectures are discussed, with a particular emphasis on achieving collision-less movement in both simulation and the real environment. Presented results demonstrate successful sim-to-real transfer, showcasing similar movements executed by an RL-trained model in both simulated and real setups.

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cs.RO

Penulis (4)

Jaume Albardaner

Alberto San Miguel

Néstor García

Magí Dalmau-Moreno

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Albardaner, J., Miguel, A.S., García, N., Dalmau-Moreno, M. (2024). Sim-to-Real gap in RL: Use Case with TIAGo and Isaac Sim/Gym. https://arxiv.org/abs/2403.07091

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Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓