Codes in this repository is deployed to Nano dev board. This sub-project serves to define the control strategy for the robot.
pip install pynetworktables
pip install schema
pip install bokeh
pip3 install torch==1.3.1+cpu torchvision==0.4.2+cpu -f https://download.pytorch.org/whl/torch_stable.html
- UI 界面,用户交互
- 控制算法
- 向 Roborio 发送指令
- 占用管理、优先级策略。
- WEB Dashboard
task | coffee days | field days |
---|---|---|
底盘控制测试 | 1 | 1 |
电机测试模块 | 0.5 | 0.5 |
方框图,数据缓存显示 | 2 | 0 |
所有机器部件的控制模块 | 0 | 2 |
基本的算法和策略 | 5 | 10 |
计算机视觉部分 | 5 | 10 |
- Websocket
- 控制能动
- config 工作的
- 一个用来测试电机的 module 0.5+0.5
- Benchmark 方框图+数据的缓存和显示 2+0
- python 不管连接,只管 raw data
- 实时/最后
- 4W 吃进每一个配件,写 module, mapping 通过 config 0+2
- CV inf+inf (与刘宏逸同吃同睡)
- (双目)图像定位 3
- 找球
- 瞄准 发射模块
- 转盘模块
- 杠杆的平衡调整
系统架构:ARM x64
CUDA: supported
# Prep
apt update
apt install python3.7
apt-get install python3-pip
# System Package
sudo apt install -y git cmake
sudo apt install -y libatlas-base-dev gfortran
sudo apt install -y libhdf5-serial-dev hdf5-tools
## ERROR python.h not found -> Looks like you haven't properly installed the header files and static libraries for python dev. Use your package manager to install them system-wide.
sudo apt install -y python3-dev
sudo apt install -y python3.7-dev
# ALL using python3.7 installed
pip install cmake
pip install testresources
pip install -U setuptools
# CUDA
echo "# Add 64-bit CUDA library & binary paths:" >> ~/.bashrc
echo "export CUBA_HOME=/usr/local/cuda-10.0" >> ~/.bashrc
echo "export PATH=/usr/local/cuda-<cuda_version>/bin:$PATH" >> ~/.bashrc
echo "export
LD_LIBRARY_PATH=/usr/local/cuda-<cuda_version>/lib64:$LD_LIBRARY_PATH" >>
~/.bashrc
$ source ~/.bashrc
# Python Virtual Environment
pip install virtualenv
cd ~
mkdir FRC
cd FRC
virtualenv FRC_ENV
source FRC_ENV/bin/activate
#ref https://devtalk.nvidia.com/default/topic/1049071/pytorch-for-jetson-nano-version-1-3-0-now-available/
# Install py3.6 pytorch + torchvision
NANO接硬盘
EMMC
# swap memory
# Download, Compile and Install pyTorch
sudo nvpmodel -m 0
~/jetson_clocks.sh
export USE_NCCL=0
$ export USE_DISTRIBUTED=0
$ export TORCH_CUDA_ARCH_LIST="5.3;6.2;7.2"
export PYTORCH_BUILD_VERSION=<version> # without the leading 'v', e.g. 1.3.0 for PyTorch v1.3.0
$ export PYTORCH_BUILD_NUMBER=1
pip install scikit-build --user
pip install ninja --user
git clone --recursive --branch v<x.x.x> http://github.com/pytorch/pytorch
cd pytorch
pip install -r requirements.txt
python setup.py bdist_wheel
# Install torch precompiled
wget https://nvidia.box.com/shared/static/phqe92v26cbhqjohwtvxorrwnmrnfx1o.whl -O torch-1.3.0-cp36-cp36m-linux_aarch64.whl
pip3 install numpy torch-1.3.0-cp36-cp36m-linux_aarch64.whl
pip install <wheel>
# Install Torchvision
apt-get install libjpeg-dev #zlib1g-dev
git clone --branch v0.4.2 https://github.com/pytorch/vision torchvision
cd torchvision
python setup.py install
# Detectron Prerequisite
ycocotools: pip install cython; pip install 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
## opencv
opencv is pre-installed.
#for virtualenv
cp /usr/local/lib/python2.7/dist-packages/cv* ./lib/python2.7/site-packages/
# Prereq Lib
## dir: FRC
source activate FRC_DEV36/bin/activate
pip install websockets
pip install configparser
pip install asyncio
pip install schema
pip install pynetworktables
pip install bokeh # -> numpy dependency
git clone -b dev https://cheetahbots8015@dev.azure.com/cheetahbots8015/2020_infinite_recharge/_git/2020_IR_NANO
cd 2020_IR_NANO
python main.py
- Python SSL
- python环境
- opencv
- 安装pytorch
https://www.cnblogs.com/ggjucheng/archive/2013/01/14/2859613.html
opencv 降采样 average