6 accepted papers
Vision-Language Model (VLM) is now an important component to enable robust robot manipulation. Yet, using it to translate human instructions into an action-resolvable intermediate representation often needs a tradeoff between VLM-comprehensibility and generalizability. Inspired by context-free gramm
Observing that the key for robotic action planning is to understand the target-object motion when its associated part is manipulated by the end effector, we propose to generate the 3D object-part scene flow and extract its transformations to solve the action trajectories for diverse embodiments. The
Robotic bin packing is a challenging task, requiring compactly packing objects in a container and also efficiently performing the computation, such that the robot arm need not wait too long before taking action. In this work, we introduce PPN-Pack, a novel learning-based approach to improve the effi
Robotic bin packing is very challenging, especially when considering practical needs such as object variety and packing compactness. This paper presents SDF-Pack, a new approach based on signed distance field (SDF) to model the geometric condition of objects in a container and compute the object pla…
Action assessment is a task of assessing the performance of an action. It is widely applicable to many real-world scenarios such as medical treatment and sporting events. However, existing methods for action assessment are mostly limited to individual actions, especially lacking modeling of the asym…
We present a new model to assess the performance of actions from videos, through graph-based joint relation modelling. Previous works mainly focused on the whole scene including the performer's body and background, yet they ignored the detailed joint interactions. This is insufficient for fine-grain…