# Unlocking Sim2Real for a Robotic Arm with RL Accelerated by AMD Instinct GPUs

**URL:** <https://devcommunity.amd.com/t/unlocking-sim2real-for-a-robotic-arm-with-rl-accelerated-by-amd-instinct-gpus/1113>\
**Category:** Physical AI & Robotics\
**Tags:** instinct, ai, tutorial, learning, physical-ai-robotics\
**Created:** [September 30, 2026, 11:43am UTC](https://devcommunity.amd.com/t/unlocking-sim2real-for-a-robotic-arm-with-rl-accelerated-by-amd-instinct-gpus/1113 "2026-09-30T11:43:09Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Ayllee\_AMD](https://dub1.discourse-cdn.com/amd/user_avatar/devcommunity.amd.com/ayllee_amd/32/290_2.png) [@Ayllee\_AMD](https://devcommunity.amd.com/u/Ayllee_AMD)\
**Post date:** [September 30, 2026, 11:43am UTC](https://devcommunity.amd.com/t/unlocking-sim2real-for-a-robotic-arm-with-rl-accelerated-by-amd-instinct-gpus/1113/1 "2026-09-30T11:43:09Z")

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![Unlocking Sim2Real for a Robotic Arm with RL Accelerated by AMD Instinct GPUs](https://global.discourse-cdn.com/amd/original/2X/0/0585a0f4677e46c4516988db1db012e2dd6b1566.jpeg)

Training a policy in simulation and transferring those weights to a real robot (sim2real) is a highly desirable goal in physical AI. Simulation scales data collection far beyond what a single robot can provide, but mismatches in physics and in the software stack make transfer difficult.

In this blog post, we train a pick-and-lift policy for a UFactory XArm-6 with reinforcement learning on AMD Instinct GPUs, then deploy the same network on the real arm with a classical perception front-end in place of privileged simulator state.

If you’re building physical AI / robotics workloads on AMD hardware, this is a deployable-today walkthrough for closing the sim-to-real gap.

🔗 Read the full article here:  
[Unlocking Sim2Real for a Robotic Arm with RL Accelerated by AMD Instinct GPUs](https://rocm.blogs.amd.com/artificial-intelligence/sim2real-rl-instinct/README.html)