diff --git a/README.md b/README.md index 0bda6a2..91c0d98 100644 --- a/README.md +++ b/README.md @@ -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).

new_env

@@ -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!