This repo contains simulation scripts and assets for the ICRA 2021 paper, "Sim-to-real for robotic tactile sensing via physics-based simulation and learned latent projections." (paper | website)

The script provides a simple example of how to import the BioTac assets into NVIDIA Isaac Gym, launch an FEM simulation with multiple indenters across multiple parallel environments, and extract useful features (net forces, nodal coordinates, and element-wise stresses).

• Clone repo
• Download NVIDIA Isaac Gym
  • Follow provided instructions to create and activate rlgpu Conda environment for Isaac Gym
• Install h5py package via Conda

• Execute sim_biotac.py
  • See code for available command line switches
• View results.hdf5
  • File structure is timestep / feature / environment / data

• Error: cannot open shared object file
  • Add /home/username/anaconda3/envs/rlgpu/lib to LD_LIBRARY_PATH
• Warning: Degenerate or inverted tet
  • Safely ignore

• For questions related to NVIDIA Isaac Gym, see official forum