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674 changes: 674 additions & 0 deletions LICENCE

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## 代码结构

- camera_model:相机模型定义文件
- config:参数文件
- feature_tracker:前端特征处理器文件
- pose_graph:回环检测模块文件
- vins_estimator:后端位姿估计器文件

## 使用

- 首先将所有文件放入工作空间src中,编译并source,可以参照plvins.md安装依赖库
- 根据需要,修改launch文件读取的参数文件及参数文件内容(默认处理EuRoc数据集)
- 启动点线特征处理器
- ```Go
roslaunch feature_tracker feature_tracker.launch # 分别启动点线特征处理器
roslaunch feature_tracker plfeature_tracker.launch # 启动点线联合特征处理器,适用于sp-sold2网络
```
- 启动后端位姿估计和轨迹重建
- ```Go
roslaunch plvins_estimator estimator.launch #运行后轨迹文件会保存到指定路径下
```

对于不同的数据集,需要参照config中的文件调整参数,并在launch中指明

## 自定义前端

自定义前端包括点/线的提取、匹配方法,按照以下几个步骤进行自定义:

- 参照 feature_tracker/scripts/utils_point/superpoint/model.py 和 feature_tracker/scripts/utils_line/sold2/model.py,继承BaseExtractModel(含有extract方法)和BaseMatchModel(含有match方法),自定义提取或匹配方法
- 按照格式将继承类写入 feature_tracker/scripts/utils_point/my_point_model.py 和 feature_tracker/scripts/utils_line/my_line_model.py 的实例化函数中
- 根据自己定义的方法名和参数名,写入config中
- 此时程序将根据名字找到自定义方法,利用参数实例化并执行自定义前端特征处理器
- 预定义的前端方法包括:点提取(superpoint),点匹配(nnm, superglue);线提取(sold2),线匹配(wunsch),以及点线联合推理的方法(sp-sold2)
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