A 3D generation startup reaches RSS with GPU-accelerated robust trajectory optimization
机器之心 · wechat · 2026-07-23
A 3D generation company lands an RSS robotics award nomination with GPU-accelerated motion planning
Machine Heart reports that Imagery/3D generation company Shadowmind Technology was nominated for RSS 2026's Outstanding Paper Award for its robotics paper, cuNRTO: GPU-Accelerated Nonlinear Robust Trajectory Optimization.
- The work addresses the sim-to-real gap by making trajectories robust to bounded uncertainty instead of trying to perfectly simulate reality.
- It reformulates nonlinear robust trajectory optimization so the inner loop can run efficiently on GPU, replacing an interior-point-heavy pipeline with DR-style splitting and then a full ADMM version.
- Reported speedups are dramatic: a unicycle task drops from 30,423 s to 218 s; a quadrotor task from 13,374 s to 200 s; and a Franka arm task from 3,949 s to 152 s.
- The paper claims 100% constraint satisfaction across 2,000 Monte Carlo rollouts and includes a real-robot validation on Robotarium hardware.
- The article frames this as part of a broader research arc from 3D generation and Sim-Ready assets to physical-world-ready robot control.
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