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t-dt-2024-radar repositorydebug_map kalman_filter vision_interface cluster dynamic_cloud localization livox_interfaces livox_ros2_driver livox_sdk_vendor tdt_vision rosbag_player |
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Repository Summary
Checkout URI | https://github.com/t-dt-algorithm-2024/t-dt-2024-radar.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2024-11-12 |
Dev Status | UNMAINTAINED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Packages
Name | Version |
---|---|
debug_map | 0.0.0 |
kalman_filter | 0.0.0 |
vision_interface | 0.0.0 |
cluster | 0.0.0 |
dynamic_cloud | 0.0.0 |
localization | 0.0.0 |
livox_interfaces | 0.0.1 |
livox_ros2_driver | 0.0.1 |
livox_sdk_vendor | 0.0.1 |
tdt_vision | 0.0.0 |
rosbag_player | 0.0.0 |
README
# 版本和发布记录
**v0.0.1beta**
- 初始化仓库,加入基础内容,初版README
**v1.0**
- 加入开源技术报告链接
**v1.1**
- TensorRT 10 API 支持
- Ubuntu 24.04 支持 (Jazzy分支)
- 删除rosbag_player包,改用 [rosbag2](https://github.com/ros2/rosbag2/tree/jazzy?tab=readme-ov-file#using-with-composition) 进程内通信 (Jazzy分支)
# 项目介绍
东北大学RM2024雷达技术报告 [https://bbs.robomaster.com/wiki/260375/27115](https://bbs.robomaster.com/wiki/260375/27115)
本项目通过激光雷达和单目相机的目标检测,进行传感器后融合,实现了传感器之间的完全解耦合,避免了联合标定带来的误差,同时开发难度不随传感器数量增加而增加。~~(如果和你关系好的队伍不幸被淘汰了,可以把相机/雷达直接借过来用。)~~
**如果你没有激光雷达,也可以直接使用本项目的单目相机方案 (在RM2023的0.6m误差规则下取得了最高91%的准确率,荣获2023年雷达MVP)**
图1:配准效果
CONTRIBUTING
No CONTRIBUTING.md found.
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