A mapping system for autonomous valet parking(AVP).

Developing [--------> 40 % ---------------]

• Simulation
  • static world
  • dynamic agents
• Data pretreatment
  • vidar point cloud
  • bev image
  • NN based Semantic segmentation
  • occupied grid for submap
• Front End
  • Odom with scale rate
  • IMU & Encoder Fusion
• Back End
  • 3D PGO using ceres
  • 3D PGO using g2o
• Loop Closing
  • Object based loop closing
• Mapping & Visualization
  • Cloud map
  • Grid map
  • Vector map

Clone and build

mkdir -p ~/catkin_ws/src
cd ~/catkin_ws/src
git clone [email protected]:adin-pro/avp_mapping.git
cd ..
catkin_make
source devel/setup.zsh

Prepare model & materials for simulation

unzip parklot.tar.gz and copy extraced files to .gazebo/models/

tar -zxvf parklot.tar.gz;
cp -r parklot/ .gazebo/models/

Launch Simulation world and rviz

replace word_dir in avp_mapping/config/global_config.yaml with your own path

roslaunch avp_mapping online_simulation.launch

Control your robot

roslaunch avp_mapping robot_control.launch
rosrun avp_mapping avp_data_pretreat_node

Launch Mapping Nodes

roslaunch avp_mapping online_mapping.launch

Use rosbag to record data, and then use offline mode for more efficient program development

roslaunch avp_mapping offline_mode.launch

Loop Closing

Trajs after Pose Graph Optimization

Mapping

Before Optimization

After Optimization

1. Code FrameWork https://github.com/Little-Potato-1990/localization_in_auto_driving
2. Gazebo simulation environment https://github.com/TurtleZhong/AVP-SLAM-SIM
3. Robot Control Module https://github.com/huchunxu/ros_exploring
4. Implementation Reference https://github.com/liuguitao/AVP-SLAM-PLUS