2 citations · 4 across the 6 of their papers we have counts for
10 papers · 1 filter
IOSG: Image-driven Object Searching and Grasping
Houjian Yu, Xibai Lou, Yang Yang +1
When robots retrieve specific objects from cluttered scenes, such as home and warehouse environments, the target objects are often partially occluded or completely hidden. Robots a…
Active Mass Distribution Estimation from Tactile Feedback
Jiacheng Yuan, Changhyun Choi, Ellad B. Tadmor +1
In this work, we present a method to estimate the mass distribution of a rigid object through robotic interactions and tactile feedback. This is a challenging problem because of th…
Self-Supervised Interactive Object Segmentation Through a Singulation-and-Grasping Approach
Houjian Yu, Changhyun Choi
Instance segmentation with unseen objects is a challenging problem in unstructured environments. To solve this problem, we propose a robot learning approach to actively interact wi…
Interactive Robotic Grasping with Attribute-Guided Disambiguation
Yang Yang, Xibai Lou, Changhyun Choi
Interactive robotic grasping using natural language is one of the most fundamental tasks in human-robot interaction. However, language can be a source of ambiguity, particularly wh…
Learning Object Relations with Graph Neural Networks for Target-Driven Grasping in Dense Clutter
Xibai Lou, Yang Yang, Changhyun Choi
Robots in the real world frequently come across identical objects in dense clutter. When evaluating grasp poses in these scenarios, a target-driven grasping system requires knowled…
Attribute-Based Robotic Grasping with One-Grasp Adaptation
Yang Yang, Yuanhao Liu, Hengyue Liang +2
Robotic grasping is one of the most fundamental robotic manipulation tasks and has been actively studied. However, how to quickly teach a robot to grasp a novel target object in cl…