A5002735167- Robotics and Sensor-Based Localization
- Robotic Path Planning Algorithms
- Optical measurement and interference techniques
- Soft Robotics and Applications
- 3D Surveying and Cultural Heritage
- Advanced Vision and Imaging
- Advanced Neural Network Applications
- Indoor and Outdoor Localization Technologies
Zhejiang University
2023
In this paper, we propose an efficient continuous-time LiDAR-Inertial-Camera Odometry, utilizing non-uniform B-splines to tightly couple measurements from the LiDAR, IMU, and camera. contrast uniform B-spline-based methods, our B-spline approach offers significant advantages in terms of achieving real-time efficiency high accuracy. This is accomplished by dynamically adaptively placing control points, taking into account varying dynamics motion. To enable fusion heterogeneous data within a...
This letter presents a novel method for geographical localization by registering satellite maps with LiDAR point clouds. includes Transformer-based 2D-3D matching network called D-GLSNet that directly matches the clouds and images through end-to-end learning. Without need feature detection, provides accurate pixel-to-point association between images. And then, we can easily calculate horizontal offset <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML"...
This paper proposes a real-time, versatile Simultaneous Localization and Mapping (SLAM) object localization system, which fuses measurements from LiDAR, camera, Inertial Measurement Unit (IMU), Global Positioning System (GPS). Our system can locate itself in an unknown environment build scene map based on we also track obtain the global location of objects interest. Precisely, our SLAM subsystem consists following four parts: LiDAR-inertial odometry, Visual-inertial GPS-inertial pose graph...
This paper proposes a LiDAR-Inertial SLAM with efficiently extracted planes, which couples explicit planes in the odometry to improve accuracy and mapping for consistency. The proposed method consists of three parts: an efficient Point <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\boldsymbol{\rightarrow\text{Line}\rightarrow \text{Plane}}$</tex> extraction algorithm, LiDAR-Inertial-Plane tightly coupled odometry, global plane-aided mapping....