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transformer-sru-lys

Transformer-SRU LiDAR navigation for Unitree G1: Isaac Lab training, MuJoCo validation, and ROS 2 deployment.

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GITHUB · launched Oct 13, 2026 · 22 upvotes (top 58%)

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Could you build this?

No End-to-end LiDAR reinforcement learning navigation on a physical Unitree G1 humanoid robot involves advanced robotics control, sim-to-real transfer, and physical hardware deployment.

What it would actually take: Requires setting up massively parallel reinforcement learning pipelines in NVIDIA Isaac Lab with point cloud encoders and Transformer-SRU temporal policy networks. The difficult challenges are designing reward functions for stable bipedal locomotion, extensive domain randomization to overcome the sim-to-real gap, and low-latency ROS 2 C++ nodes to execute policy inference on the robot's onboard compute. It necessitates specialized expertise in humanoid kinematics, RL sim-to-real transfer, and real-time robotics systems.

Competitors

Other products that read as similar to this one : 149 launches clear the similarity bar, closest 8 shown.

Attention rank: #77 of 150 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 330 days after the earliest competitor.

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