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hdl_people_tracking

hdl_people_tracking is a ROS package for real-time people tracking using a 3D LIDAR. It first performs Haselich's clustering technique to detect human candidate clusters, and then applies Kidono's person classifier to eliminate false detections. The detected clusters are tracked by using Kalman filter with a contant velocity model.

Video:
hdl_people_tracking

Requirements

hdl_people_tracking requires the following libraries:

  • OpenMP
  • PCL 1.7

The following ros packages are required:

Example

Bag file (recorded in an outdoor environment):

rosparam set use_sim_time true
roslaunch hdl_people_tracking hdl_people_tracking.launch
roscd hdl_localization/rviz
rviz -d hdl_localization.rviz
rosbag play --clock hdl_400.bag

[NOTE]:

If it doesn't work well, change ndt_neighbor_search_method in hdl_localization.launch to "DIRECT1". It makes the scan matching significantly fast, but a little bit unstable.

If your bagfile is static (velodyne device is fixed) try with the following launch file without any localization needs:

rosparam set use_sim_time true
roslaunch hdl_people_tracking hdl_people_tracking_static.launch

Related packages

Papers

Kenji Koide, Jun Miura, and Emanuele Menegatti, A Portable 3D LIDAR-based System for Long-term and Wide-area People Behavior Measurement, Advanced Robotic Systems, 2019 [link].

Contact

Kenji Koide, [email protected]

Active Intelligent Systems Laboratory, Toyohashi University of Technology, Japan [URL]
Robot Innovation Research Center, National Institute of Advanced Industrial Science and Technology, Japan [URL]