69 citations · 75 across the 3 of their papers we have counts for
8 papers
Assemble Them All: Physics-Based Planning for Generalizable Assembly by Disassembly
Yunsheng Tian, Jie Xu, Yichen Li +5
Assembly planning is the core of automating product assembly, maintenance, and recycling for modern industrial manufacturing. Despite its importance and long history of research, p…
Learning Dense Reward with Temporal Variant Self-Supervision
Yuning Wu, Jieliang Luo, Hui Li
Rewards play an essential role in reinforcement learning. In contrast to rule-based game environments with well-defined reward functions, complex real-world robotic applications, s…
Building-GAN: Graph-Conditioned Architectural Volumetric Design Generation
Kai-Hung Chang, Chin-Yi Cheng, Jieliang Luo +3
Volumetric design is the first and critical step for professional building design, where architects not only depict the rough 3D geometry of the building but also specify the progr…
RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers
Saeid Asgari Taghanaki, Jieliang Luo, Ran Zhang +3
The 3D deep learning community has seen significant strides in pointcloud processing over the last few years. However, the datasets on which deep models have been trained have larg…
A Learning Approach to Robot-Agnostic Force-Guided High Precision Assembly
Jieliang Luo, Hui Li
In this work we propose a learning approach to high-precision robotic assembly problems. We focus on the contact-rich phase, where the assembly pieces are in close contact with eac…
Dynamic Experience Replay
Jieliang Luo, Hui Li
We present a novel technique called Dynamic Experience Replay (DER) that allows Reinforcement Learning (RL) algorithms to use experience replay samples not only from human demonstr…