From bd8d8afe956a3e98f58d63856570c69cbf01915c Mon Sep 17 00:00:00 2001 From: "ziv.lin" <730470317@qq.com> Date: Sat, 1 Jan 2022 16:30:04 +0800 Subject: [PATCH] [Fix] change image width, fix bugs when viewing README.md on moblie platform. --- README.md | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index 12f3e68..5d10d49 100755 --- a/README.md +++ b/README.md @@ -8,8 +8,8 @@ **R3LIVE** is a novel LiDAR-Inertial-Visual sensor fusion framework, which takes advantage of measurement of LiDAR, inertial, and visual sensors to achieve robust and accurate state estimation. R3LIVE is built upon our previous work [R2LIVE](https://github.com/hku-mars/r2live), is contained of two subsystems: the LiDAR-inertial odometry (LIO) and the visual-inertial odometry (VIO). The LIO subsystem ([FAST-LIO](https://github.com/hku-mars/FAST_LIO)) takes advantage of the measurement from LiDAR and inertial sensors and builds the geometric structure of (i.e. the position of 3D points) global maps. The VIO subsystem utilizes the data of visual-inertial sensors and renders the map's texture (i.e. the color of 3D points).
  Our preprint paper is available [here](https://github.com/hku-mars/r3live/blob/master/papers/R3LIVE:%20A%20Robust%2C%20Real-time%2C%20RGB-colored%2C%20LiDAR-Inertial-Visual%20tightly-coupled%20stateEstimation%20and%20mapping%20package.pdf), with our accompanying videos are now available on YouTube (click below images to open) and Bilibili[1](https://www.bilibili.com/video/BV1d341117d6?share_source=copy_web), [2](https://www.bilibili.com/video/BV1e3411q7Di?share_source=copy_web).
-video -video +video +video
## 2. What can R3LIVE do? @@ -17,34 +17,34 @@ ### 2.1 Strong robustness in various challenging scenarios R3LIVE is robust enough to work well in various of LiDAR-degenerated scenarios (see following figures):
- - - - + + + +
And even in simultaneously LiDAR degenerated and visual texture-less environments (see Experiment-1 of our [paper](https://github.com/hku-mars/r3live/blob/master/papers/R3LIVE:%20A%20Robust%2C%20Real-time%2C%20RGB-colored%2C%20LiDAR-Inertial-Visual%20tightly-coupled%20stateEstimation%20and%20mapping%20package.pdf)).
-video -video +video +video
### 2.2 Real-time RGB maps reconstruction R3LIVE is able to reconstruct the precise, dense, 3D, RGB-colored maps of surrounding environment in real-time (watch this [video](https://youtu.be/j5fT8NE5fdg)).
- - - - -video + + + + +video
### 2.3 Ready for 3D applications To make R3LIVE more extensible, we also provide a series of offline utilities for reconstructing and texturing meshes, which further reduce the gap between R3LIVE and various 3D applications (watch this [video](https://youtu.be/4rjrrLgL3nk)).
-video -video - +video +video +
## 3. Prerequisites