Zobrazeno 1 - 10
of 209
pro vyhledávání: '"Choi, Changhyun"'
Autor:
Li, Mingen, Choi, Changhyun
Publikováno v:
2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024, pp. 5183-5189
Manipulation of deformable Linear objects (DLOs), including iron wire, rubber, silk, and nylon rope, is ubiquitous in daily life. These objects exhibit diverse physical properties, such as Young$'$s modulus and bending stiffness.Such diversity poses
Externí odkaz:
http://arxiv.org/abs/2410.23428
The language-guided robot grasping task requires a robot agent to integrate multimodal information from both visual and linguistic inputs to predict actions for target-driven grasping. While recent approaches utilizing Multimodal Large Language Model
Externí odkaz:
http://arxiv.org/abs/2409.19457
Learning multi-object dynamics from visual data using unsupervised techniques is challenging due to the need for robust, object representations that can be learned through robot interactions. This paper presents a novel framework with two new archite
Externí odkaz:
http://arxiv.org/abs/2310.04617
Adversarial object rearrangement in the real world (e.g., previously unseen or oversized items in kitchens and stores) could benefit from understanding task scenes, which inherently entail heterogeneous components such as current objects, goal object
Externí odkaz:
http://arxiv.org/abs/2309.15378
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 are thus required to search, identify a target object, and successfully
Externí odkaz:
http://arxiv.org/abs/2308.05821
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 the complexity of physical dynamics modeling and the action dependencies
Externí odkaz:
http://arxiv.org/abs/2303.01010
Autor:
Choi, Changhyun
As robotic systems move from well-controlled settings to increasingly unstructured environments, they are required to operate in highly dynamic and cluttered scenarios. Finding an object, estimating its pose, and tracking its pose over time within su
Externí odkaz:
http://hdl.handle.net/1853/53003
Autor:
Yu, Houjian, Choi, Changhyun
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 with novel objects and collect each object's training label for further
Externí odkaz:
http://arxiv.org/abs/2207.09314
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 when there are ambiguous visual or linguistic contents. This paper inves
Externí odkaz:
http://arxiv.org/abs/2203.08037
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 knowledge of spatial relations between scene objects (e.g., proximity, adjace
Externí odkaz:
http://arxiv.org/abs/2203.00875