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Junfeng Wu

18 papers hereh-index 214 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author3
  • last author13

Across the 18 of 18 papers where every author was matched, so the position is known.

fields
  • cs.RO13
  • eess.SY2
  • cs.CV1
  • eess.SP1
  • stat.AP1
same name
  • Junfeng Wu — 29 papers, h 23
  • Junfeng Wu — 10 papers, h 8
  • Junfeng Wu — 3 papers, h 1
  • Junfeng Wu — 3 papers, h 2
  • Junfeng Wu — 2 papers
  • Junfeng Wu — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedGlobal and Asymptotically Efficient Localization from Range Measurements

26 citations · 29 across the 16 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.RO2026

\textbf{PLATO}: \emph{Preintegration Learning from Accurate Trajectory Observations} for Neural Inertial Odometry

Haoying Li, Qihang Liu, Yifan Peng +2

Neural inertial odometry has demonstrated strong potential for motion estimation in challenging environments, yet inertial-only preintegration remains sensitive to IMU bias and unc…

cs.RO2026

Cooperative-ORCA*: Real-Time Proactive Deadlock Avoidance for Continuous-Space Multi-Agent Navigation

Junfeng Wu, Jiaqi Chen, Hongkun Lyu +2

Multi-Agent Path Finding (MAPF) is a problem that requires computing collision-free paths for a set of agents from their start locations to designated goal locations. The problem h…

cs.RO2026

A High-accuracy Event-based Underwater SLAM System

Yifan Peng, Qihang Liu, Haoying Li +3

While event cameras offer immense potential for underwater SLAM, existing Time Surface (TS)-based methods prove highly unreliable when deployed underwater. Fluctuating camera veloc…

cs.RO2026

Provably Guaranteed Polytopic Uncertainty Quantification for SLAM

Guangyang Zeng, Yulong Gao, Yuan Shen +4

In safety-critical robotics applications, guaranteed and practical uncertainty quantification (UQ) in perception is vital. Many existing works either offer no formal containment gu…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.