From the 1 of 6 linked papers with an AI index.
6 papers
PAC-DP: PAC-Bayesian Diffusion Policy Learning
Mohammad Hasan Yeganegi, Dian Yu, Andrea Del Prete +2
Diffusion Policies (DPs) are able to perform complex manipulation tasks. However, DPs are typically trained by minimizing a denoising objective, which provides limited control over…
Safe-Night VLA: Seeing the Unseen via Thermal-Perceptive Vision-Language-Action Models for Safety-Critical Manipulation
Dian Yu, Qingchuan Zhou, Bingkun Huang +2
The paper introduces Safe-Night VLA, a robot manipulation system that combines long-wave infrared thermal sensing with a vision‑language backbone and adds safety guarantees via con…
DynaRetarget: Dynamically-Feasible Retargeting using Sampling-Based Trajectory Optimization
Victor Dhedin, Ilyass Taouil, Shafeef Omar +4
In this paper, we introduce DynaRetarget, a complete pipeline for retargeting human motions to humanoid control policies. The core component of DynaRetarget is a novel Sampling-Bas…
Guided Discovery of New Behaviors using Diffusion Policies
Dian Yu, Sebastian Sanokowski, Majid Khadiv
Diffusion models have become a powerful tool for generative modeling in robotics, with diffusion policies excelling at modeling multimodal action-trajectory distributions. However,…
UniConFlow: A Unified Constrained Flow-Matching Framework for Certified Motion Planning
Zewen Yang, Xiaobing Dai, Dian Yu +4
Generative models have become increasingly powerful tools for robot motion generation, enabling flexible and multimodal trajectory generation across various tasks. Yet, most existi…
SafeFlow: Safe Robot Motion Planning with Flow Matching via Control Barrier Functions
Xiaobing Dai, Zewen Yang, Dian Yu +4
Recent advances in generative modeling have led to promising results in robot motion planning, particularly through diffusion and flow matching (FM)-based models that capture compl…