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‎CMakeLists.txt

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cmake_minimum_required(VERSION 2.8.3)
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project(reinforcement_learning_navigation)
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## Add support for C++11, supported in ROS Kinetic and newer
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# add_definitions(-std=c++11)
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## Find catkin macros and libraries
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## if COMPONENTS list like find_package(catkin REQUIRED COMPONENTS xyz)
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## is used, also find other catkin packages
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find_package(catkin REQUIRED COMPONENTS
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)
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## System dependencies are found with CMake's conventions
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# find_package(Boost REQUIRED COMPONENTS system)
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## Uncomment this if the package has a setup.py. This macro ensures
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## modules and global scripts declared therein get installed
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## See http://ros.org/doc/api/catkin/html/user_guide/setup_dot_py.html
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# catkin_python_setup()
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################################################
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## Declare ROS messages, services and actions ##
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################################################
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## To declare and build messages, services or actions from within this
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## package, follow these steps:
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## * Let MSG_DEP_SET be the set of packages whose message types you use in
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## your messages/services/actions (e.g. std_msgs, actionlib_msgs, ...).
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## * In the file package.xml:
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## * add a build_depend tag for "message_generation"
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## * add a build_depend and a run_depend tag for each package in MSG_DEP_SET
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## * If MSG_DEP_SET isn't empty the following dependency has been pulled in
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## but can be declared for certainty nonetheless:
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## * add a run_depend tag for "message_runtime"
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## * In this file (CMakeLists.txt):
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## * add "message_generation" and every package in MSG_DEP_SET to
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## find_package(catkin REQUIRED COMPONENTS ...)
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## * add "message_runtime" and every package in MSG_DEP_SET to
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## catkin_package(CATKIN_DEPENDS ...)
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## * uncomment the add_*_files sections below as needed
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## and list every .msg/.srv/.action file to be processed
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## * uncomment the generate_messages entry below
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## * add every package in MSG_DEP_SET to generate_messages(DEPENDENCIES ...)
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## Generate messages in the 'msg' folder
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# add_message_files(
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# FILES
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# Message1.msg
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# Message2.msg
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# )
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## Generate services in the 'srv' folder
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# add_service_files(
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# FILES
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# Service1.srv
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# Service2.srv
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# )
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## Generate actions in the 'action' folder
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# add_action_files(
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# FILES
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# Action1.action
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# Action2.action
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# )
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## Generate added messages and services with any dependencies listed here
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# generate_messages(
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# DEPENDENCIES
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# std_msgs # Or other packages containing msgs
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# )
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################################################
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## Declare ROS dynamic reconfigure parameters ##
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################################################
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## To declare and build dynamic reconfigure parameters within this
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## package, follow these steps:
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## * In the file package.xml:
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## * add a build_depend and a run_depend tag for "dynamic_reconfigure"
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## * In this file (CMakeLists.txt):
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## * add "dynamic_reconfigure" to
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## find_package(catkin REQUIRED COMPONENTS ...)
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## * uncomment the "generate_dynamic_reconfigure_options" section below
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## and list every .cfg file to be processed
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## Generate dynamic reconfigure parameters in the 'cfg' folder
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# generate_dynamic_reconfigure_options(
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# cfg/DynReconf1.cfg
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# cfg/DynReconf2.cfg
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# )
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###################################
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## catkin specific configuration ##
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###################################
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## The catkin_package macro generates cmake config files for your package
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## Declare things to be passed to dependent projects
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## INCLUDE_DIRS: uncomment this if you package contains header files
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## LIBRARIES: libraries you create in this project that dependent projects also need
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## CATKIN_DEPENDS: catkin_packages dependent projects also need
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## DEPENDS: system dependencies of this project that dependent projects also need
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catkin_package(
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# INCLUDE_DIRS include
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# LIBRARIES reinforcement_learning_navigation
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# CATKIN_DEPENDS ridgeback_gazebo ridgeback_navigation
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# DEPENDS system_lib
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)
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###########
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## Build ##
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###########
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## Specify additional locations of header files
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## Your package locations should be listed before other locations
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# include_directories(include)
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include_directories(
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${catkin_INCLUDE_DIRS}
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)
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## Declare a C++ library
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# add_library(${PROJECT_NAME}
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# src/${PROJECT_NAME}/reinfocement_learning_navigation.cpp
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# )
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## Add cmake target dependencies of the library
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## as an example, code may need to be generated before libraries
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## either from message generation or dynamic reconfigure
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# add_dependencies(${PROJECT_NAME} ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
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## Declare a C++ executable
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## With catkin_make all packages are built within a single CMake context
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## The recommended prefix ensures that target names across packages don't collide
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# add_executable(${PROJECT_NAME}_node src/reinforcement_learning_navigaation_node.cpp)
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## Rename C++ executable without prefix
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## The above recommended prefix causes long target names, the following renames the
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## target back to the shorter version for ease of user use
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## e.g. "rosrun someones_pkg node" instead of "rosrun someones_pkg someones_pkg_node"
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# set_target_properties(${PROJECT_NAME}_node PROPERTIES OUTPUT_NAME node PREFIX "")
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## Add cmake target dependencies of the executable
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## same as for the library above
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# add_dependencies(${PROJECT_NAME}_node ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
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## Specify libraries to link a library or executable target against
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# target_link_libraries(${PROJECT_NAME}_node
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# ${catkin_LIBRARIES}
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# )
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#############
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## Install ##
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#############
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# all install targets should use catkin DESTINATION variables
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# See http://ros.org/doc/api/catkin/html/adv_user_guide/variables.html
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## Mark executable scripts (Python etc.) for installation
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## in contrast to setup.py, you can choose the destination
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# install(PROGRAMS
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# scripts/my_python_script
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# DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
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# )
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## Mark executables and/or libraries for installation
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# install(TARGETS ${PROJECT_NAME} ${PROJECT_NAME}_node
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# ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
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# LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
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# RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
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# )
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## Mark cpp header files for installation
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# install(DIRECTORY include/${PROJECT_NAME}/
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# DESTINATION ${CATKIN_PACKAGE_INCLUDE_DESTINATION}
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# FILES_MATCHING PATTERN "*.h"
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# PATTERN ".svn" EXCLUDE
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# )
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## Mark other files for installation (e.g. launch and bag files, etc.)
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# install(FILES
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# # myfile1
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# # myfile2
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# DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
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# )
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#############
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## Testing ##
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#############
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## Add gtest based cpp test target and link libraries
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# catkin_add_gtest(${PROJECT_NAME}-test test/test_reinfocement_learning_navigation.cpp)
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# if(TARGET ${PROJECT_NAME}-test)
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# target_link_libraries(${PROJECT_NAME}-test ${PROJECT_NAME})
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# endif()
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## Add folders to be run by python nosetests
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# catkin_add_nosetests(test)

‎README.md

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## Reinforced Imitation Open Source Repo
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Stay tuned! We are currently preparing our code for open-sourcing.
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Reinforced Imitation
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====================
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This repository contains the tensorflow implementation for training a reinforcement learning based map-less navigation model, as described in the paper:\
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[Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations](https://arxiv.org/abs/1805.07095)
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# Requirements
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1. Ubuntu
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2. Python 2.7
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3. [ROS Indigo](http://wiki.ros.org/indigo) or [ROS Kinetic](http://wiki.ros.org/kinetic)
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4. Stage-ros simulator, with `add_pose_sub` enabled. Can be found in this [branch](https://github.com/ros-simulation/stage_ros/tree/add_pose_sub) of the repository.
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# Training the Model
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1. First run the stage simulator:
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`roslaunch reinforcement_learning_navigation stage_sim.launch`
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2. In a separate terminal, run the training code:
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`rosrun reinforcement_learning_navigation train_cpo.py --output_name $experiment_name$`\
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In order to use pre-trained weights from imitation learning, add the arguments `--jump_start 1 --model_init $path_to_policy_weights$`
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# Citation
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If you use our code in your research, please cite our paper.
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```
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@ARTICLE{pfeiffer2018ral,
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author={M. Pfeiffer and S. Shukla and M. Turchetta and C. Cadena Lerma and A. Krause and R. Siegwart and J. Nieto},
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journal={IEEE Robotics and Automation Letters},
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title={{Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations}},
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year={2018},
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volume={3},
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number={4},
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pages={4423-4430}
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}
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```
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# References
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Our training model uses Constrained Policy Optimization : \[[Paper](https://arxiv.org/abs/1705.10528)\] \[[Code](https://github.com/jachiam/cpo)\]

‎README.md~

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<<<<<<< HEAD
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## Reinforce Imitation Open Source Repo
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=======
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## Reinforced Imitation Open Source Repo
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>>>>>>> origin/fix/name
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Stay tuned! We are currently preparing our code for open-sourcing.

‎initial_weights/simple_model/checkpoint

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model_checkpoint_path: "final"
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all_model_checkpoint_paths: "snap-40000"
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all_model_checkpoint_paths: "snap-80000"
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all_model_checkpoint_paths: "final"

‎initial_weights/simple_model/eval/events.out.tfevents.1528469029.hyrax

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‎launch/stage_sim.launch

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<!--
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Turtlebot navigation simulation:
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- stage
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- map_server
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- move_base
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- static map
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- amcl
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- rviz view
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-->
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<launch>
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<arg name="base" default="$(optenv TURTLEBOT_BASE kobuki)"/> <!-- create, rhoomba -->
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<arg name="stacks" default="$(optenv TURTLEBOT_STACKS hexagons)"/> <!-- circles, hexagons -->
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<arg name="3d_sensor" default="$(optenv TURTLEBOT_3D_SENSOR kinect)"/> <!-- kinect, asus_xtion_pro -->
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<!-- Name of the map to use (without path nor extension) and initial position -->
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<arg name="map_file" default="$(find reinforcement_learning_navigation)/maps/train_env.yaml "/> <!-- robopark_plan -->
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<arg name="world_file" default="$(find reinforcement_learning_navigation)/maps/stage/train_env.world"/>
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<arg name="initial_pose_x" default="0.0"/>
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<arg name="initial_pose_y" default="0.0"/>
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<arg name="initial_pose_a" default="0.0"/>
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<param name="/use_sim_time" value="true"/>
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<!-- ******************** Stage ******************** -->
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<!--
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Publishes transforms:
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/base_link -> /base_laser
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/base_footprint -> /base_link (identity)
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/odom -> base_footprint
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Publishes topics:
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/odom : odometry data from the simulated odometry
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/base_scan : laser data from the simulated laser
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/base_pose_ground_truth : the ground truth pose
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Parameters:
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base_watchdog_timeout : time (s) after receiving the last command on cmd_vel before stopping the robot
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Args:
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-g : run in headless mode.
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-->
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<node pkg="stage_ros" type="stageros" name="stageros" args="-g $(arg world_file)" respawn="true">
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<param name="base_watchdog_timeout" value="0.2"/>
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<remap from="odom" to="odom"/>
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<remap from="base_pose_ground_truth" to="base_pose_ground_truth"/>
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<!--remap from="cmd_vel" to="mobile_base/commands/velocity"/-->
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<!--remap from="base_scan" to="scan"/-->
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<!--remap from="base_scan_0" to="front/scan"/-->
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<!--remap from="base_scan_1" to="rear/scan"/-->
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</node>
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<!-- ***************** Robot Model ***************** -->
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<include file="$(find turtlebot_bringup)/launch/includes/robot.launch.xml">
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<arg name="base" value="$(arg base)" />
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<arg name="stacks" value="$(arg stacks)" />
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<arg name="3d_sensor" value="$(arg 3d_sensor)" />
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</include>
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<node name="joint_state_publisher" pkg="joint_state_publisher" type="joint_state_publisher">
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<param name="use_gui" value="false"/>
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</node>
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<!-- Command Velocity multiplexer -->
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<node pkg="nodelet" type="nodelet" name="mobile_base_nodelet_manager" args="manager"/>
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<node pkg="nodelet" type="nodelet" name="cmd_vel_mux" args="load yocs_cmd_vel_mux/CmdVelMuxNodelet mobile_base_nodelet_manager">
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<param name="yaml_cfg_file" value="$(find turtlebot_bringup)/param/mux.yaml"/>
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<remap from="cmd_vel_mux/output" to="mobile_base/commands/velocity"/>
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</node>
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<!-- ************** Navigation *************** -->
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<!--include file="$(find turtlebot_navigation)/launch/includes/move_base.launch.xml"/-->
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<!-- ****** Maps ***** -->
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<!--node name="map_server" pkg="map_server" type="map_server" args="$(arg map_file)"-->
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<!--param name="frame_id" value="/map"/-->
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<!--/node-->
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<!--include file="$(find turtlebot_navigation)/launch/includes/amcl/amcl.launch.xml"-->
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<!--arg name="scan_topic" value="scan"/-->
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<!--arg name="use_map_topic" value="true"/-->
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<!--arg name="initial_pose_x" value="$(arg initial_pose_x)"/-->
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<!--arg name="initial_pose_y" value="$(arg initial_pose_y)"/-->
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<!--arg name="initial_pose_a" value="$(arg initial_pose_a)"/-->
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<!--/include-->
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<!-- **************** Visualisation **************** -->
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<!--node name="rviz" pkg="rviz" type="rviz" args="-d $(find turtlebot_stage)/rviz/robot_navigation.rviz"/-->
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</launch>

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