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TJU_Lu 2025-06-17 10:57:07 +08:00
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@ -115,7 +115,7 @@ cd YOPO
rviz -d yopo.rviz
```
Left: Random Forest(maze_type=5); Right: 3D Perlin (maze_type=1).
Left: Random Forest (maze_type=5); Right: 3D Perlin (maze_type=1).
<p align="center">
<img src="docs/new_env.gif" alt="new_env" />
</p>
@ -196,6 +196,9 @@ python test_yopo_ros.py --use_tensorrt=1
+ You may want to use the position controller like traditional planners in real flight to make it compatible with your controller. You should change `plan_from_reference: False` to `True` at the end of `test_yopo_ros.py`. You can test the changes in simulation using the position controller: `roslaunch so3_quadrotor_simulator simulator_position_control.launch
`
## RKNN Deployment
On the RK3566 clip (only 1 TOPS NPU), after deploying with RKNN and INT8 quantization, inference takes only about 20 ms (backbone: ResNet-14). The update of deployment on RK3566 or RK3588 is coming soon.
## Finally
We are still working on improving and refactoring the code to improve the readability, reliability, and efficiency. For any technical issues, please feel free to contact me (lqzx1998@tju.edu.cn) 😀 We are very open and enjoy collaboration!