DoF grasp detection has been a fundamental and challenging problem in robotic vision.
While previous works have focused on ensuring grasp stability, they often do not consider …

Affordance detection is a challenging problem with a wide variety of robotic applications.
Traditional affordance detection methods are limited to a predefined set of affordance labels …

Affordance detection and pose estimation are of great importance in many robotic
applications. Their combination helps the robot gain an enhanced manipulation capability …

Solving the analytical inverse kinematics (IK) of redundant manipulators in real time is a
difficult problem in robotics since its solution for a given target pose is not unique. Moreover …

Foundation models such as ChatGPT have made significant strides in robotic tasks due to
their universal representation of real-world domains. In this paper, we leverage foundation …

Affordance detection presents intricate challenges and has a wide range of robotic
applications. Previous works have faced limitations such as the complexities of 3D object …

Grasp detection is a persistent and intricate challenge with various industrial applications.
Recently many methods and datasets have been proposed to tackle the grasp detection …

We introduce Reactive Action and Motion Planner (RAMP), which combines the strengths of
sampling-based and reactive approaches for motion planning. In essence, RAMP is a …

Real-time applications for autonomous operations depend largely on fast and robust vision-
based localization systems. Since image processing tasks require processing large amounts …

Grasp detection is a fundamental robotic task critical to the success of many industrial
applications. However, current language-driven models for this task often struggle with …