26 citations · 34 across the 14 of their papers we have counts for
15 papers
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…
Spatiotemporal Calibration of Doppler Velocity Logs for Underwater Robots
Hongxu Zhao, Guangyang Zeng, Yunling Shao +2
The calibration of extrinsic parameters and clock offsets between sensors for high-accuracy performance in underwater SLAM systems remains insufficiently explored. Existing methods…
GeVI-SLAM: Gravity-Enhanced Stereo Visua Inertial SLAM for Underwater Robots
Yuan Shen, Yuze Hong, Guangyang Zeng +4
Accurate visual inertial simultaneous localization and mapping (VI SLAM) for underwater robots remains a significant challenge due to frequent visual degeneracy and insufficient in…
Theoretical Guarantees for AOA-based Localization: Consistency and Asymptotic Efficiency
Shenghua Hu, Guangyang Zeng, Wenchao Xue +2
We study the problem of signal source localization using angle of arrival (AOA) measurements. We begin by presenting verifiable geometric conditions for sensor deployment that ensu…
RSS-Based Localization: Ensuring Consistency and Asymptotic Efficiency
Shenghua Hu, Guangyang Zeng, Wenchao Xue +3
We study the problem of signal source localization using received signal strength measurements. We begin by presenting verifiable geometric conditions for sensor deployment that en…
Bias-Eliminated PnP for Stereo Visual Odometry: Provably Consistent and Large-Scale Localization
Guangyang Zeng, Yuan Shen, Ziyang Hong +4
In this paper, we first present a bias-eliminated weighted (Bias-Eli-W) perspective-n-point (PnP) estimator for stereo visual odometry (VO) with provable consistency. Specifically,…
BESTAnP: Bi-Step Efficient and Statistically Optimal Estimator for Acoustic-n-Point Problem
Wenliang Sheng, Hongxu Zhao, Lingpeng Chen +6
We consider the acoustic-n-point (AnP) problem, which estimates the pose of a 2D forward-looking sonar (FLS) according to n 3D-2D point correspondences. We explore the nature of th…
Optimal camera-robot pose estimation in linear time from points and lines
Guangyang Zeng, Biqiang Mu, Qingcheng Zeng +4
Camera pose estimation is a fundamental problem in robotics. This paper focuses on two issues of interest: First, point and line features have complementary advantages, and it is o…
Fast Estimation of Relative Transformation Based on Fusion of Odometry and UWB Ranging Data
Yuan Fu, Zheng Zhang, Guangyang Zeng +3
In this paper, we investigate the problem of estimating the 4-DOF (three-dimensional position and orientation) robot-robot relative frame transformation using odometers and distanc…
Consistent and Optimal Solution to Camera Motion Estimation
Guangyang Zeng, Qingcheng Zeng, Xinghan Li +4
Given 2D point correspondences between an image pair, inferring the camera motion is a fundamental issue in the computer vision community. The existing works generally set out from…
Efficient Invariant Kalman Filter for Inertial-based Odometry with Large-sample Environmental Measurements
Xinghan Li, Haoying Li, Guangyang Zeng +4
A filter for inertial-based odometry is a recursive method used to estimate the pose from measurements of ego-motion and relative pose. Currently, there is no known filter that gua…
Consistent and Asymptotically Efficient Localization from Range-Difference Measurements
Guangyang Zeng, Biqiang Mu, Ling Shi +2
We consider signal source localization from range-difference measurements. First, we give some readily-checked conditions on measurement noises and sensor deployment to guarantee t…
CPnP: Consistent Pose Estimator for Perspective-n-Point Problem with Bias Elimination
Guangyang Zeng, Shiyu Chen, Biqiang Mu +2
The Perspective-n-Point (PnP) problem has been widely studied in both computer vision and photogrammetry societies. With the development of feature extraction techniques, a large n…
Global and Asymptotically Efficient Localization from Range Measurements
Guangyang Zeng, Biqiang Mu, Jiming Chen +2
We consider the range-based localization problem, which involves estimating an object's position by using sensors, hoping that as the number of sensors increases, the estim…
Low-complexity Distributed Detection with One-bit Memory Under Neyman-Pearson Criterion
Guangyang Zeng, Xiaoqiang Ren, Junfeng Wu
We consider a multi-stage distributed detection scenario, where sensors and a fusion center (FC) are deployed to accomplish a binary hypothesis test. At each time stage, local…