Seeking Prior Projects or Advice on Sim-to-Real RL for WLKATA Mirobot using Isaac Lab

Hi everyone,

I’m a 3rd-year undergraduate student currently working on a reinforcement learning project. My goal is to train a WLKATA Mirobot (6-DOF) in NVIDIA Isaac Lab for a “reach and stop” task and successfully transfer the policy to the real robot (Sim-to-Real).

I am specifically focusing on overcoming the mechanical limitations (such as backlash and joint friction) of the Mirobot through Domain Randomization and System Identification.

Before I dive deeper into designing the environment, I wanted to ask the community:

1. Are there any prior projects or open-source repositories that have successfully integrated the Mirobot with Isaac Sim/Lab?
2. For those who have worked with low-cost 6-DOF arms, what are your best tips for Domain Randomization parameters to bridge the reality gap effectively?
3. Are there any specific Reward Shaping strategies you would recommend to ensure the robot stops precisely at the target without jittering?

I’m currently using Ubuntu 22.04 and ROS 2 Jazzy. If anyone has worked on something similar, I would love to hear about your experience or even “copy” (with credits!) some of your environment configurations to speed up my learning.

Thanks in advance!