open-source hardware

.gitignore

@@ -22,7 +22,6 @@ _site
 # saved
 run/saved/*
 !run/saved/YOPO_1
-run/yopo_trt.pth
 externals/
 
 #logs
@@ -31,4 +30,8 @@ run/utils/*.csv
 # dataset
 /run/yopo_sim/*
 /run/rknn_quantization/*
+/run/*.onnx
+/run/*.pt
+/run/*.pth
+/run/*.rknn
 

README.md

@@ -10,8 +10,12 @@ Some realworld experiment: [YouTube](https://youtu.be/LHvtbKmTwvE), [bilibili](h
 <table>
     <td align="center" style="border: none;"><img src="docs/realworld_1.gif" alt="Fig1" style="width: 100%;"></td>
     <td align="center" style="border: none;"><img src="docs/realworld_2.gif" alt="Fig2" style="width: 100%;"></td>
+    <td align="center" style="border: none; width: 23%;"><img src="docs/platform.gif" alt="Fig3" style="width: 100%;"></td>
 </table>
 
+### Hardware:
+Our drone designed by [@Mioulo](https://github.com/Mioulo) is also open-source. The hardware components are listed in [hardware_list.pdf](hardware/hardware_list.pdf), and the SolidWorks file of carbon fiber frame can be found in [/hardware](hardware/).
+
 ## Introduction:
 We propose **a learning-based planner for autonomous navigation in obstacle-dense environments** which intergrats (i) perception and mapping, (ii) front-end path searching, and (iii) back-end optimization of classical methods into a single network.