Skip to content

TempleRAIL/pedsim_ros_with_gazebo

Repository files navigation

Introduction:

A 3D human-robot interaction Gazebo simulator for our paper "DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles"(arXiv) in IEEE Transactions on Robotics (T-RO) 2023, and "Towards Safe Navigation Through Crowded Dynamic Environments" in IROS 2021, which is modified from https://github.com/srl-freiburg/pedsim_ros. The aim of the simulator is to provide a close-to-real-world simulated environment for mobile robots navigating around pedestrians. Detailed usage can be found at our DRL-VO control policy.

Here is a GIF showing how this simulator works:

simulation_demo

Modifications:

This simulator is based on the Gazebo simulator and PEDSIM library, which uses the social forces model to guide the motion of individual pedestrians. The main modifications from https://github.com/srl-freiburg/pedsim_ros are as follows:

  • Integrate Pedsim_ros with the 3D gazebo simulator and turtlebot2 robot;
  • Add an additional social force to the robot and other pedestrians;
  • Add different test scenarios for robot navigation;
  • Change the meshes of spawned agents in the gazebo to make them look like real humans;


Requirements

  • Ubuntu system >= 16.04
  • ROS-Kinetic/Melodic/Noetic

Installation

The default version is ROS Noetic.

cd ~
mkdir catkin_ws
cd catkin_ws
mkdir src
cd src
git clone https://github.com/TempleRAIL/robot_gazebo.git
git clone https://github.com/TempleRAIL/pedsim_ros_with_gazebo.git
wget https://raw.githubusercontent.com/zzuxzt/turtlebot2_noetic_packages/master/turtlebot2_noetic_install.sh
chmod +x turtlebot2_noetic_install.sh 
sudo sh turtlebot2_noetic_install.sh 
cd ..
catkin_make

Usage:

More detailed usage can be found in our DRL-VO control policy.

roslaunch pedsim_simulator robot.launch
roslaunch robot_gazebo view_navigation.launch

Acknowledgements

All contributors from https://github.com/srl-freiburg/pedsim_ros.

Citation

@article{xie2023drl,
  author={Xie, Zhanteng and Dames, Philip},
  journal={IEEE Transactions on Robotics}, 
  title={DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles}, 
  year={2023},
  volume={39},
  number={4},
  pages={2700-2719},
  doi={10.1109/TRO.2023.3257549}
}

@inproceedings{xie2021towards,
  title={Towards safe navigation through crowded dynamic environments},
  author={Xie, Zhanteng and Xin, Pujie and Dames, Philip},
  booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={4934--4940},
  year={2021},
  organization={IEEE}
}