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Nicola Scianca

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#artificial intelligence Preprint Oct 2026

YUBI-Real2Sim: 3DGS Scene Verification for Reliable Policy Evaluation

Evaluating VLA policies on real robots is costly, time-consuming, and difficult to reproduce, making real-to-sim simulation essential for scalable evaluation. While 3D Gaussian Splatting (3DGS) enables rapid real-to-sim scene generation, the reconstruction quality required for reliable policy evaluation remains unquant...

Hiroki Nishizawa, Takehiko Ohkawa, Nicola Scianca et al. · 0 citations
Preprint Oct 2026

RoboPace: Contact-Aware Time-Optimal Retiming for Action-Chunk Policies

Robot manipulation data collection has been shifting from teleoperation toward robot-free demonstrations, through interfaces such as the Universal Manipulation Interface (UMI) or directly from human hands. Vision-Language-Action (VLA) policies trained on such data inherit the demonstrator's timing. Yet human timing doe...

Mimo Shirasaka, Takehiko Ohkawa, Takuya Okubo et al. · 0 citations
Open access Oct 2026

Feasibility-Based Convexification of MPC Footstep Constraints for Humanoid Gait Generation

Model Predictive Control is an effective tool for robust humanoid gait generation in complex 3D environments. This challenging operating condition typically results in non-convex footstep constraints which, if directly included in the optimization problem, would introduce significant computation overhead. We present a...

Andrew S. Habib, Nicola Scianca, L. Lanari et al. · 0 citations

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