12 citations · 15 across the 19 of their papers we have counts for
20 papers
TempFit: Panoptic Symbol Spotting via Template Fitting
Honghao Xu, Hao Wang, Xiang Liu +4
In this paper, we introduce TempFit, a novel approach for the problem of Panoptic Symbol Spotting on CAD drawings. Existing methods treat symbol spotting as a per-primitive classif…
PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation
Yuhang Huang, Xuan Lv, Junyan Xu +25
World foundation models (WFMs) are powerful simulators, yet they predominantly operate in a single-view setting and lack the multi-view 3D consistency required for robotic manipula…
IMR-LLM: Industrial Multi-Robot Task Planning and Program Generation using Large Language Models
Xiangyu Su, Juzhan Xu, Oliver van Kaick +2
In modern industrial production, multiple robots often collaborate to complete complex manufacturing tasks. Large language models (LLMs), with their strong reasoning capabilities,…
Learning Flexible Job Shop Scheduling under Limited Buffers and Material Kitting Constraints
Shishun Zhang, Juzhan Xu, Yidan Fan +4
The Flexible Job Shop Scheduling Problem (FJSP) originates from real production lines, while some practical constraints are often ignored or idealized in current FJSP studies, amon…
Embodied Intelligence for Flexible Manufacturing: A Survey
Kai Xu, Hang Zhao, Ruizhen Hu +4
Driven by breakthroughs in next-generation artificial intelligence, embodied intelligence is rapidly advancing into industrial manufacturing. In flexible manufacturing, industrial…
AdaPower: Specializing World Foundation Models for Predictive Manipulation
Yuhang Huang, Shilong Zou, Jiazhao Zhang +3
World Foundation Models (WFMs) offer remarkable visual dynamics simulation capabilities, yet their application to precise robotic control remains limited by the gap between generat…
RoboBPP: Benchmarking Robotic Online Bin Packing with Physics-based Simulation
Zhoufeng Wang, Hang Zhao, Juzhan Xu +8
Physical feasibility in 3D bin packing is a key requirement in modern industrial logistics and robotic automation. With the growing adoption of industrial automation, online bin pa…
PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation
Wenxuan Li, Hang Zhao, Zhiyuan Yu +4
While non-prehensile manipulation (e.g., controlled pushing/poking) constitutes a foundational robotic skill, its learning remains challenging due to the high sensitivity to comple…
LaDi-WM: A Latent Diffusion-based World Model for Predictive Manipulation
Yuhang Huang, Jiazhao Zhang, Shilong Zou +3
Predictive manipulation has recently gained considerable attention in the Embodied AI community due to its potential to improve robot policy performance by leveraging predicted sta…
Deliberate Planning of 3D Bin Packing on Packing Configuration Trees
Hang Zhao, Juzhan Xu, Kexiong Yu +4
Online 3D Bin Packing Problem (3D-BPP) has widespread applications in industrial automation. Existing methods usually solve the problem with limited resolution of spatial discretiz…
Learning the Geometric Mechanics of Robot Motion Using Gaussian Mixtures
Ruizhen Hu, Shai Revzen
Data-driven models of robot motion constructed using principles from Geometric Mechanics have been shown to produce useful predictions of robot motion for a variety of robots. For…
G3Flow: Generative 3D Semantic Flow for Pose-aware and Generalizable Object Manipulation
Tianxing Chen, Yao Mu, Zhixuan Liang +8
Recent advances in imitation learning for 3D robotic manipulation have shown promising results with diffusion-based policies. However, achieving human-level dexterity requires seam…
LLM-enhanced Scene Graph Learning for Household Rearrangement
Wenhao Li, Zhiyuan Yu, Qijin She +5
The household rearrangement task involves spotting misplaced objects in a scene and accommodate them with proper places. It depends both on common-sense knowledge on the objective…
FRI-Net: Floorplan Reconstruction via Room-wise Implicit Representation
Honghao Xu, Juzhan Xu, Zeyu Huang +3
In this paper, we introduce a novel method called FRI-Net for 2D floorplan reconstruction from 3D point cloud. Existing methods typically rely on corner regression or box regressio…
LGTM: Local-to-Global Text-Driven Human Motion Diffusion Model
Haowen Sun, Ruikun Zheng, Haibin Huang +3
In this paper, we introduce LGTM, a novel Local-to-Global pipeline for Text-to-Motion generation. LGTM utilizes a diffusion-based architecture and aims to address the challenge of…
Spatial and Surface Correspondence Field for Interaction Transfer
Zeyu Huang, Honghao Xu, Haibin Huang +3
In this paper, we introduce a new method for the task of interaction transfer. Given an example interaction between a source object and an agent, our method can automatically infer…
Learning Cross-hand Policies for High-DOF Reaching and Grasping
Qijin She, Shishun Zhang, Yunfan Ye +2
Reaching-and-grasping is a fundamental skill for robotic manipulation, but existing methods usually train models on a specific gripper and cannot be reused on another gripper. In t…
Synchronized Dual-arm Rearrangement via Cooperative mTSP
Wenhao Li, Shishun Zhang, Sisi Dai +4
Synchronized dual-arm rearrangement is widely studied as a common scenario in industrial applications. It often faces scalability challenges due to the computational complexity of…
InterFusion: Text-Driven Generation of 3D Human-Object Interaction
Sisi Dai, Wenhao Li, Haowen Sun +5
In this study, we tackle the complex task of generating 3D human-object interactions (HOI) from textual descriptions in a zero-shot text-to-3D manner. We identify and address two k…
Learning Dual-arm Object Rearrangement for Cartesian Robots
Shishun Zhang, Qijin She, Wenhao Li +4
This work focuses on the dual-arm object rearrangement problem abstracted from a realistic industrial scenario of Cartesian robots. The goal of this problem is to transfer all the…