Project
DEFTACTGYM: A Reinforcement Learning Testbed for Deformable Object Manipulation Using Visuotactile Sensory Data
Chanyoung Ahn, Bonggyeong Park, Jaehwi Jang, Minwoo Cho, Jeongho Ha, Daehyung Park
RIRO Lab @ KAIST Dec 2022
We aim to create a simulated testbed for training and assessing deformable object manipulation skills. This testbed requires tactile data to detect occluded deformation to acquire skills. In this work, we introduce a tactile testbed, DetactGym, with custom-built tactile sensors. We implement tactile sensors as a combination of a rigid trigger and a force-reading part to address the IsaacSim simulator’s inability to read contact forces in deformable. The trigger transmits the contact force to the sensor upon interaction with the target deformable. We highlight the effectiveness of tactile information over visual cues in handling deformable objects while minimizing deformation.
