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agentic_rsr

Agentic RSR: Real-to-Sim-to-Real through Scene Reconstruction and Execution-Grounded Robot Policies

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GITHUB · launched Oct 14, 2026 · 10 upvotes (top 94%)

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Could you build this?

No The project is a robotics research pipeline that combines multi-view depth reconstruction, segmentation, physics simulation, and sim-to-real policy transfer, and it needs a CUDA GPU and real robot hardware.

What it would actually take: The stack spans VGGT-style depth and camera estimation, SAM-style segmentation, URDF-based metric alignment, MuJoCo simulation, Blender scene building, and reinforcement or imitation learning for manipulation policies. Reproducing it requires robotics and ML research expertise, GPU compute, access to gated checkpoints, and a physical robot for real-world validation.

Competitors

Other products that read as similar to this one : 3043 launches clear the similarity bar, closest 8 shown.

Attention rank: #2819 of 3044 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 350 days after the earliest competitor.

Other launches for this product

More details
External ID
1418439456
Company
n/a
Product
agentic_rsr
Website domain
github.io
Cohort
n/a
Upvotes percentile
0.06
All tags
n/a
AI summary
real-to-sim-to-real framework for robot policies
Manually corrected
No