activity
20212024
most citedA Right Invariant Extended Kalman Filter for Object based SLAM

3 citations · 6 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2024

Multi-cam Multi-map Visual Inertial Localization: System, Validation and Dataset

Yufei Wei, Fuzhang Han, Yanmei Jiao +9

Robot control loops require causal pose estimates that depend only on past and present measurements. At each timestep, controllers compute commands using the current pose without w…

cs.RO2023★ 1 cited

NGEL-SLAM: Neural Implicit Representation-based Global Consistent Low-Latency SLAM System

Yunxuan Mao, Xuan Yu, Kai Wang +3

Neural implicit representations have emerged as a promising solution for providing dense geometry in Simultaneous Localization and Mapping (SLAM). However, existing methods in this…

cs.RO2022★ 1 cited

FEJ-VIRO: A Consistent First-Estimate Jacobian Visual-Inertial-Ranging Odometry

Shenhan Jia, Yanmei Jiao, Zhuqing Zhang +2

In recent years, Visual-Inertial Odometry (VIO) has achieved many significant progresses. However, VIO methods suffer from localization drift over long trajectories. In this paper,…

cs.RO2022

Map-based Visual-Inertial Localization: Consistency and Complexity

Zhuqing Zhang, Yanmei Jiao, Shoudong Huang +2

Drift-free localization is essential for autonomous vehicles. In this paper, we address the problem by proposing a filter-based framework, which integrates the visual-inertial odom…

cs.RO2022★ 1 cited

Toward Consistent and Efficient Map-based Visual-inertial Localization: Theory Framework and Filter Design

Zhuqing Zhang, Yang Song, Shoudong Huang +2

This paper focuses on designing a consistent and efficient filter for map-based visual-inertial localization. First, we propose a new Lie group with its algebra, based on which a n…

cs.RO2021★ 3 cited

A Right Invariant Extended Kalman Filter for Object based SLAM

Yang Song, Zhuqing Zhang, Jun Wu +3

With the recent advance of deep learning based object recognition and estimation, it is possible to consider object level SLAM where the pose of each object is estimated in the SLA…