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

Jaume Albardaner, Alberto San Miguel, Néstor García, Magí Dalmau-Moreno

Abstract

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.

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

Abstract

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.
Paper Structure (12 sections, 8 theorems, 72 equations, 2 figures, 2 tables)

This paper contains 12 sections, 8 theorems, 72 equations, 2 figures, 2 tables.

Key Result

proposition 1

Assume $H'(0)=0$ and $H(0)=0$. Set: If $\gamma < - \lambda < \delta$, the solution $\overline{u}$ is non-zero:

Figures (2)

  • Figure 1: This is the caption of the figure displaying a white eagle and a white horse on a snow field
  • Figure 2: This is the caption of the figure displaying a white eagle and a white horse on a snow field

Theorems & Definitions (16)

  • proposition 1
  • proof
  • corollary 1
  • proof
  • lemma 1
  • proof
  • theorem 1: Ghoussoub-Preiss
  • definition 1
  • proposition 2
  • proof
  • ...and 6 more