5 papers
Self-Supervised Learning of Object Segmentation from Unlabeled RGB-D Videos
Shiyang Lu, Yunfu Deng, Abdeslam Boularias +1
This work proposes a self-supervised learning system for segmenting rigid objects in RGB images. The proposed pipeline is trained on unlabeled RGB-D videos of static objects, which…
ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation
Chaitanya Mitash, Fan Wang, Shiyang Lu +4
This paper introduces Amazon Robotic Manipulation Benchmark (ARMBench), a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse. Auto…
Online Object Model Reconstruction and Reuse for Lifelong Improvement of Robot Manipulation
Shiyang Lu, Rui Wang, Yinglong Miao +2
This work proposes a robotic pipeline for picking and constrained placement of objects without geometric shape priors. Compared to recent efforts developed for similar tasks, where…
Safe and Effective Picking Paths in Clutter given Discrete Distributions of Object Poses
Rui Wang, Chaitanya Mitash, Shiyang Lu +2
Picking an item in the presence of other objects can be challenging as it involves occlusions and partial views. Given object models, one approach is to perform object pose estimat…
Factored Pose Estimation of Articulated Objects using Efficient Nonparametric Belief Propagation
Karthik Desingh, Shiyang Lu, Anthony Opipari +1
Robots working in human environments often encounter a wide range of articulated objects, such as tools, cabinets, and other jointed objects. Such articulated objects can take an i…