activity
20202026
most citedAttention-SLAM: A Visual Monocular SLAM Learning from Human Gaze

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

collaborators
Showing cs.ROShow all

7 papers · 1 filter

cs.RO2026

Efficient Minimal Solvers for Relative Pose Estimation in Autonomous Driving Applications

Tao Li, Liang Liu, Jianli Han +1

With the advancement of visual sensing systems, computer vision is playing an increasingly important role in autonomous driving and robot navigation. Relative pose estimation in mu…

cs.RO2025

DLBAcalib: Robust Extrinsic Calibration for Non-Overlapping LiDARs Based on Dual LBA

Han Ye, Yuqiang Jin, Jinyuan Liu +3

Accurate extrinsic calibration of multiple LiDARs is crucial for improving the foundational performance of three-dimensional (3D) map reconstruction systems. This paper presents a…

cs.RO2024

MLP-SLAM: Multilayer Perceptron-Based Simultaneous Localization and Mapping

Taozhe Li, Wei Sun

The Visual Simultaneous Localization and Mapping (V-SLAM) system has seen significant development in recent years, demonstrating high precision in environments with limited dynamic…

cs.RO2023

PLV-IEKF: Consistent Visual-Inertial Odometry using Points, Lines, and Vanishing Points

Tong Hua, Tao Li, Liang Pang +4

In this paper, we propose an Invariant Extended Kalman Filter (IEKF) based Visual-Inertial Odometry (VIO) using multiple features in man-made environments. Conventional EKF-based V…

cs.RO2023

Sky-GVINS: a Sky-segmentation Aided GNSS-Visual-Inertial System for Robust Navigation in Urban Canyons

Jie Yin, Tao Li, Hao Yin +2

Integrating Global Navigation Satellite Systems (GNSS) in Simultaneous Localization and Mapping (SLAM) systems draws increasing attention to a global and continuous localization so…

cs.RO20232 cited

PIEKF-VIWO: Visual-Inertial-Wheel Odometry using Partial Invariant Extended Kalman Filter

Tong Hua, Tao Li, Ling Pei

Invariant Extended Kalman Filter (IEKF) has been successfully applied in Visual-inertial Odometry (VIO) as an advanced achievement of Kalman filter, showing great potential in sens…