4 accepted papers
Force sensing is a crucial modality for Vision-Language-Action (VLA) frameworks, as it enables fine-grained perception and dexterous manipulation in contact-rich tasks. We present Force-Distilled VLA (FD-VLA), a novel framework that integrates force awareness into contact-rich manipulation without r…
Recent advancements in robotics have focused on developing foundation models capable of generating both actions and future states. Typically, these policies leverage world models to depict human-like imagination. However, most methods remain confined to the 2D domain, where they forecast only the fi…
Imitation learning has emerged as an effective paradigm for training visuo-motor policies in robotic manipulation. In real-world scenarios, visuo-motor policies are required to be effective, sample-efficient, and capable of adapting to dynamic environments. A key factor influencing these capabilitie
This paper presents a novel approach for affordance-informed robotic manipulation by introducing 3D keypoints to enhance the understanding of object parts’ functionality. The proposed approach provides direct information about what the potential use of objects is, as well as guidance on where and ho…