Docker

.dockerignore

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+data/

Dockerfile

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+FROM tensorflow/tensorflow:1.13.1-gpu
+
+# fix nvidia public key
+RUN apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/3bf863cc.pub &&\
+    apt update
+
+# install pip and requirements
+COPY req_docker.txt ./requirements.txt
+RUN apt install -y python3-dev python3-tk &&\
+    curl -sSL https://bootstrap.pypa.io/pip/3.5/get-pip.py -o get-pip.py &&\
+    python3 get-pip.py "pip < 21.0" "setuptools < 50.0" "wheel < 1.0" &&\
+    python3 -m pip install -r requirements.txt
+
+# install ROS kinetic
+RUN sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list' &&\
+    curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | apt-key add - &&\
+    apt update &&\
+    apt install -y ros-kinetic-ros-base ros-kinetic-ros-numpy git nano &&\
+    echo "source /opt/ros/kinetic/setup.bash" >> /root/.bashrc
+
+RUN echo 'export PYTHONPATH=/badgr/src:$PYTHONPATH' >> /root/.bashrc
+
+WORKDIR /badgr
+COPY bgr.sh .

README.md

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-
 # BADGR: An Autonomous Self-Supervised Learning-Based Navigation System
 
 Gregory Kahn, Pieter Abbeel, Sergey Levine
@@ -11,6 +10,9 @@ Gregory Kahn, Pieter Abbeel, Sergey Levine
 
 Make sure you have 90GB of space available, [anaconda](https://www.anaconda.com/distribution/) installed, and [ROS](https://www.ros.org/) installed. Our installation was on Ubuntu 16.04 with ROS Kinetic.
 
+Note: [Docker](#docker) is now available as an alternative to the following system installation. This approach is recommended to avoid the hassle of installing deprecated software.
+
+
 Clone the repository and go into the folder:
 
 ```bash
@@ -106,6 +108,19 @@ change the visualizer to show bumpiness by modifying `configs/bumpy_collision_po
 python scripts/eval.py configs/bumpy_collision_position.py
 ```
 
+## Docker
+
+Docker and the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) must be installed before proceeding.
+
+First follow the standard instructions for cloning the repository and downloading the data. In the badgr directory:
+```
+docker build . -t badgr:1.13.1
+```
+After building follow the training instructions within a badgr container. Make sure to use `python3` instead of `python` A convenience script `badgr_docker` is included which brings up a container with the proper docker options. Change the volume path if badgr is not installed in your home directory.
+
+With a trained model `bgr.sh` can be run to execute the evaluation demo.
+
+
 ## FAQ
 1. If you are having issues with importing OpenCV (e.g., `ImportError: /opt/ros/kinetic/lib/python2.7/dist-packages/cv2.so: undefined symbol: PyCObject_Type`), try the following to have python look for the Python 3 OpenCV first:
 ```bash

badgr_docker

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+#! /usr/bin/env sh
+
+xhost +local:root; # for the lazy and reckless http://wiki.ros.org/docker/Tutorials/GUI
+
+# this snippet assumes badgr is in your home directory
+docker run --network host --gpus all --env="DISPLAY" --env="QT_X11_NO_MITSHM=1"  --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" -v /home/$USER/badgr:/badgr -it badgr:1.13.1 #bash -i -c "./bgr.sh";
+
+xhost -local:root;

bgr.sh

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+#!/bin/bash
+
+roscore > /dev/null 2>&1 &
+
+echo "roscore starting up..."
+while true; do
+    sleep 1
+    rostopic list > /dev/null 2>&1
+    # Check the return value of rostopic list. Keep looping until it is zero, indicing roscore is ready
+    [[ $? != 0 ]] || break
+done
+
+rosbag play -l data/rosbags/collision.bag > /dev/null 2>&1 &
+rosparam set /cost_weights "{'collision': 1.0, 'position': 0.0, 'position_sigmoid_center': 0.4, 'position_sigmoid_scale': 100., 'action_magnitude': 0.01, 'action_smooth': 0.0, 'bumpy': 0.0}";
+python3 scripts/eval.py configs/bumpy_collision_position.py;
+bash

req_docker.txt

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+catkin-pkg==0.4.13
+loguru==0.3.2
+matplotlib
+numpy
+opencv-python==4.1.1.26
+Pillow==6.1.0
+PyYAML==5.1.2
+requests==2.22.0
+rospkg==1.1.10
+tensorflow-gpu==1.13.1
+utm==0.5.0