This paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM)
designed for embodied interaction, exploring a universal 3D object understanding with 3D …

Representing robotic manipulation tasks as constraints that associate the robot and the
environment is a promising way to encode desired robot behaviors. However, it remains …

The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …

Vision Language Models (VLMs) have achieved impressive performance in 2D image
understanding, however they are still struggling with spatial understanding which is the …

Manipulation of elastoplastic objects like dough often involves topological changes such as
splitting and merging. The ability to accurately predict these topological changes that a …

Imitation learning provides an efficient way to teach robots dexterous skills; however,
learning complex skills robustly and generalizablely usually consumes large amounts of …

Bimanual manipulation is essential in robotics, yet developing foundation models is
extremely challenging due to the inherent complexity of coordinating two robot arms …

Deformable object manipulation (DOM) for robots has a wide range of applications in
various fields such as industrial, service and health care sectors. However, compared to …

Predictive models are a crucial component of many robotic systems. Yet, constructing
accurate predictive models for a variety of deformable objects, especially those with …

Deformable object manipulation presents a unique set of challenges in robotic manipulation
by exhibiting high degrees of freedom and severe self-occlusion. Choosing state …