Recent advances in learning-based robot policies have demonstrated promising progress, yet they are predom- inantly evaluated in static or quasi-static environments. In dynamic manipulation, objects and scenes continuously evolve while the robot perceives, reasons, and acts. However, recent dynamic simulation benchmark...
Mo-Han Liu, Deng-Chen Mei, Hao-Tian Xian et al.· 0 citations
Robots operating in human-centered environments are typically designed to execute explicit instructions, and most robot-learning datasets likewise pair observations with task instructions or low-level actions. Although recent work has begun to explore proactive embodied assistance, existing resources target different s...
Zhi-Hao Gu, Kenny Zhu, Yuan-Feng Wu et al.· 0 citations
This work presents VistaVLA, a novel two-stage framework that constructs a geometry- and semantics-aware 3D cognitive representation from 3D Gaussian primitives and grounds it as compact context tokens for VLA policy learning, and introduces Merge-then-Query (MtQ), a token summarization mechanism.