SlotVLA: Towards Modeling of Object-Relation Representations in Robotic Manipulation
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
The Flow has not summarised this story yet — read it at arXiv Computer Vision.
arXiv:2601. 11460v2 Announce Type: replace-cross Abstract: Learning structured task representations from human demonstrations is essential for bimanual manipulation, where action ordering, object involvement, and interaction geometry vary significantly across executions.
arXiv:2606. 08530v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve strong benchmark performance but still struggle in real-world deployment with unseen objects, background shifts, and different robot embodiments.
arXiv:2606.18363v3 Announce Type: replace-cross Abstract: Language models trained on large-scale vision-language data have demonstrated strong potential for embodied agents. Harnessing models through...
arXiv:2606.17446v2 Announce Type: replace-cross Abstract: Simulation enables scalable robot data collection, but raw 3D assets provide only geometry, lacking the semantic, interactive, and physical k...
arXiv:2512. 24125v3 Announce Type: replace-cross Abstract: General-purpose robotic systems operating in open-world environments must achieve both broad generalization and high-precision action execution, a combination that remains challenging for existing Vision-Language-Action (VLA) models.
RoboCousin is an extensible simulation platform that transforms user-provided observations into reusable assets, scenes, and expert trajectories for bimanual robotic manipulation. It converts object images into simulation-ready models with visual, collision, semantic, and physical metadata, automatically generates grasp candidates, and builds digital cousins that vary objects, backgrounds, layouts, and language instructions while preserving task-relevant affordances. The platform supports both tabletop and room-level scene construction, and the authors release RoboCousin-OBD with over 3,000 annotated objects and 50 backgrounds, generating more than one million expert trajectories across 50 tasks, with simulation and real-robot experiments demonstrating comparable annotation quality and effective sim-to-real transfer.