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Repository Summary
| Description | |
| Checkout URI | https://github.com/polarisxq/scurm_sentrynavigation.git |
| VCS Type | git |
| VCS Version | master |
| Last Updated | 2025-04-18 |
| Dev Status | UNKNOWN |
| 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 |
|---|---|
| behaviortree_cpp | 4.5.1 |
| fast_lio | 0.0.0 |
| auto_aim_interfaces | 0.0.0 |
| sensor_scan_generation | 0.0.1 |
| terrain_analysis | 0.0.1 |
| terrain_analysis_ext | 0.0.1 |
| cmd_chassis | 0.0.0 |
| control_panel | 2.3.0 |
| icp_relocalization | 1.0.0 |
| livox_ros_driver2 | 1.0.0 |
| behavior_ext_plugins | 1.1.12 |
| costmap_intensity | 1.1.12 |
| nav2_costmap_2d | 1.1.14 |
| rm_decision_cpp | 0.0.0 |
| sentry_bringup | 0.0.0 |
| rm_base | 0.0.1 |
| rm_interfaces | 0.0.1 |
| sentry_description | 0.0.0 |
README
SCURM火锅战队 24赛季哨兵导航
开源的初衷是想把自己的一些好的想法和大家一起分享，所以欢迎各位联系我和我讨论，欢迎PR，提issue🫠~
主要的创新：
-
实现FAST-LIO2的重定位模式，不需要另外运行重定位算法。算力需求小，使得整个框架在NUC12上的资源占用在30%左右；精度高，定位误差小；内存占用不会随着时间增长。
-
改进navigation2的故障恢复行为，卡住时机器人会向无碰撞的方向运动。
算法框架和思路详见技术报告
Gazebo仿真指路👉SCURM_Nav_Tutorial
Docker镜像使用方法参阅DevcontainterGuide
包说明
| Package Name | Description |
|---|---|
| ✅auto_aim_interfaces | 自瞄接口 |
| ✅autonomous_exploration_development_environment | 地形分析包terrain_analysis和terrain_analysis_ext，其他的是小工具无关紧要 |
| ✅BehaviourTree.CPP | MODIFIED BehaviourTree lib |
| ✅cmd_chassis | twist2chassis_cmd：将twist加上底盘的控制方式（如是否小陀螺），发出到串口接收的话题； twist_transformer， fake_joint用于实现底盘到云台的速度解算 |
| ✅control_panel | 模仿裁判系统发消息 |
| ✅FAST_LIO | 修改版fastlio，具备建图和重定位功能（须配合icp_relocalizatiion使用） |
| ✅icp_relocalization | 基于icp实现的重定位，须配合修改版FAST_LIO使用 |
| ✅livox_ros_driver2 | livox雷达驱动 |
| ✅nav2_plugins - behavior_ext_plugins - costmap_intensity |
Costume nav2 plugins - an enhenced back_up action that move toward free space - 2 costmap_2d layer that use intensity filed of pointcloud msg rather than height (use with terrain analysis in autonomous_exploration_development_environment) |
| ✅rm_decision_cpp | 烧饼决策系统 |
| ✅rm_interfaces | 通讯协议 |
| ✅sentry_bringup | 哨兵启动文件 |
| ✅sentry_description | 烧饼urdf |
LAUNCH
MAPPING
- launch mapping node
ros2 launch sentry_bringup mapping.launch.py
- save map
# occupancy grid map
ros2 run nav2_map_server map_saver_cli -t /projected_map -f test_map --fmt png
# save pcd
ros2 service call /map_save std_srvs/srv/Trigger
- then terminate all nodes, pcd file will be saved in /PCD/scans.pcd
MAP PROCESSING(使用CloudCompare删除建图中的人物残影, 如不处理可以跳过，但记得按照最后一步的提示替换掉pcd文件)
process pcd file
- drag the pcd file to CloudCompare(globalmap or scans.pcd), select the pointcloud in the left panel, then tools->clean->SOR filter, set the parameters (25,1 is a baseline) and apply
- select the processed pointcloud from last step, then tools->segmentation->Label Connected Components, set the parameters and apply
- pick out the CC#0(ususally this one), then tools->Other->Remove duplicate points, keep 1 point per 0.01-0.1m to reduce the size of the pointcloud
- select the processed pointcloud, then file->save as, select .pcd format
- replace the original pcd file with the processed one. Globally seach and replace ‘/home/sentry_ws/src/sentry_bringup/maps/GlobalMap.pcd’ with ‘/path/to/your/map’
LAUNCH ALL
ros2 launch sentry_bringup bringup_all_in_one.launch.py
CONTRIBUTING
No CONTRIBUTING.md found.
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