47 citations · 142 across the 8 of their papers we have counts for
9 papers
GRITS: A Spillage-Aware Guided Diffusion Policy for Robot Food Scooping Tasks
Yen-Ling Tai, Yi-Ru Yang, Kuan-Ting Yu +2
Robotic food scooping is a critical manipulation skill for food preparation and service robots. However, existing robot learning algorithms, especially learn-from-demonstration met…
MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D Images
Junwen Huang, Hao Yu, Kuan-Ting Yu +3
Recent learning methods for object pose estimation require resource-intensive training for each individual object instance or category, hampering their scalability in real applicat…
Tactile SLAM: Real-time inference of shape and pose from planar pushing
Sudharshan Suresh, Maria Bauza, Kuan-Ting Yu +3
Tactile perception is central to robot manipulation in unstructured environments. However, it requires contact, and a mature implementation must infer object models while also acco…
Realtime State Estimation with Tactile and Visual Sensing for Inserting a Suction-held Object
Kuan-Ting Yu, Alberto Rodriguez
We develop a real-time state estimation system to recover the pose and contact formation of an object relative to its environment. In this paper, we focus on the application of ins…
Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching
Andy Zeng, Shuran Song, Kuan-Ting Yu +18
This paper presents a robotic pick-and-place system that is capable of grasping and recognizing both known and novel objects in cluttered environments. The key new feature of the s…
Realtime State Estimation with Tactile and Visual sensing. Application to Planar Manipulation
Kuan-Ting Yu, Alberto Rodriguez
Accurate and robust object state estimation enables successful object manipulation. Visual sensing is widely used to estimate object poses. However, in a cluttered scene or in a ti…
Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge
Andy Zeng, Kuan-Ting Yu, Shuran Song +4
Robot warehouse automation has attracted significant interest in recent years, perhaps most visibly in the Amazon Picking Challenge (APC). A fully autonomous warehouse pick-and-pla…
A Summary of Team MIT's Approach to the Amazon Picking Challenge 2015
Kuan-Ting Yu, Nima Fazeli, Nikhil Chavan-Dafle +4
The Amazon Picking Challenge (APC), held alongside the International Conference on Robotics and Automation in May 2015 in Seattle, challenged roboticists from academia and industry…
More than a Million Ways to Be Pushed: A High-Fidelity Experimental Dataset of Planar Pushing
Kuan-Ting Yu, Maria Bauza, Nima Fazeli +1
Pushing is a motion primitive useful to handle objects that are too large, too heavy, or too cluttered to be grasped. It is at the core of much of robotic manipulation, in particul…