LapGym -- An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery

Understand

Recent advances in reinforcement learning (RL) have increased the promise of introducing cognitive assistance and automation to robot-assisted laparoscopic surgery (RALS).

• However, progress in algorithms and methods depends on the availability of standardized learning environments that represent skills relevant to RALS.
• We present LapGym, a framework for building RL environments for RALS that models the challenges posed by surgical tasks, and sofa_env, a diverse suite of 12 environments.
• Motivated by surgical training, these environments are organized into 4 tracks: Spatial Reasoning, Deformable Object Manipulation & Grasping, Dissection, and Thread Manipulation.