87 citations · 89 across the 9 of their papers we have counts for
5 papers · 1 filter
ActiveGS: Active Scene Reconstruction Using Gaussian Splatting
Liren Jin, Xingguang Zhong, Yue Pan +3
Robotics applications often rely on scene reconstructions to enable downstream tasks. In this work, we tackle the challenge of actively building an accurate map of an unknown scene…
A Dataset and Benchmark for Shape Completion of Fruits for Agricultural Robotics
Federico Magistri, Thomas Läbe, Elias Marks +9
As the world population is expected to reach 10 billion by 2050, our agricultural production system needs to double its productivity despite a decline of human workforce in the agr…
3D LiDAR Mapping in Dynamic Environments Using a 4D Implicit Neural Representation
Xingguang Zhong, Yue Pan, Cyrill Stachniss +1
Building accurate maps is a key building block to enable reliable localization, planning, and navigation of autonomous vehicles. We propose a novel approach for building accurate m…
STAIR: Semantic-Targeted Active Implicit Reconstruction
Liren Jin, Haofei Kuang, Yue Pan +2
Many autonomous robotic applications require object-level understanding when deployed. Actively reconstructing objects of interest, i.e. objects with specific semantic meanings, is…
PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving Global Map Consistency
Yue Pan, Xingguang Zhong, Louis Wiesmann +3
Accurate and robust localization and mapping are essential components for most autonomous robots. In this paper, we propose a SLAM system for building globally consistent maps, cal…