Isaac Sim Dual Robotic Arm RL System

This project focused on training two robotic arms to coordinate movement and manipulation tasks in NVIDIA Isaac Sim using reinforcement learning. Instead of relying only on hand-programmed motion, I worked on AI-based robotic control, reward design, motion stability, and robotic coordination inside simulation, with the long-term goal of adapting learned behaviors into physical hardware. The work explored how simulation can reduce physical trial-and-error while still preparing systems for the challenges of calibration, joint control, and differences between simulated and real-world physics.