46 citations · 93 across the 13 of their papers we have counts for
14 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…
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…
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…
PC-Planner: Physics-Constrained Self-Supervised Learning for Robust Neural Motion Planning with Shape-Aware Distance Function
Xujie Shen, Haocheng Peng, Zesong Yang +4
Motion Planning (MP) is a critical challenge in robotics, especially pertinent with the burgeoning interest in embodied artificial intelligence. Traditional MP methods often strugg…
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…
Neural Packing: from Visual Sensing to Reinforcement Learning
Juzhan Xu, Minglun Gong, Hao Zhang +2
We present a novel learning framework to solve the transport-and-packing (TAP) problem in 3D. It constitutes a full solution pipeline from partial observations of input objects via…
NIFT: Neural Interaction Field and Template for Object Manipulation
Zeyu Huang, Juzhan Xu, Sisi Dai +4
We introduce NIFT, Neural Interaction Field and Template, a descriptive and robust interaction representation of object manipulations to facilitate imitation learning. Given a few…
Learning High-DOF Reaching-and-Grasping via Dynamic Representation of Gripper-Object Interaction
Qijin She, Ruizhen Hu, Juzhan Xu +3
We approach the problem of high-DOF reaching-and-grasping via learning joint planning of grasp and motion with deep reinforcement learning. To resolve the sample efficiency issue i…
Shape-driven Coordinate Ordering for Star Glyph Sets via Reinforcement Learning
Ruizhen Hu, Bin Chen, Juzhan Xu +3
We present a neural optimization model trained with reinforcement learning to solve the coordinate ordering problem for sets of star glyphs. Given a set of star glyphs associated t…
TAP-Net: Transport-and-Pack using Reinforcement Learning
Ruizhen Hu, Juzhan Xu, Bin Chen +3
We introduce the transport-and-pack(TAP) problem, a frequently encountered instance of real-world packing, and develop a neural optimization solution based on reinforcement learnin…
Object-Aware Guidance for Autonomous Scene Reconstruction
Ligang Liu, Xi Xia, Han Sun +5
To carry out autonomous 3D scanning and online reconstruction of unknown indoor scenes, one has to find a balance between global exploration of the entire scene and local scanning…