^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Changelog for package multi_object_tracking_lidar ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Forthcoming ----------- * Merge pull request `#46 `_ from praveen-palanisamy/rm-topic-slash-prefix Remove topic slash prefix * Apply clang-format-10 * Rm slash prefix (deprecated in TF2) * Add note to filter NaNs in input point clouds * Contributors: Praveen Palanisamy 1.0.3 (2020-06-27) ------------------ * Merge pull request #26 from artursg/noetic-devel C++11 --> C++14 to allow compiling with later versions of PCL, ROS Neotic * Compiles under ROS Noetic * Merge pull request #25 from praveen-palanisamy/add-license-1 Add MIT LICENSE * Add LICENSE * Merge pull request #24 from mzahran001/patch-1 Fix broken hyperlink to wiki page in README * Fixing link error * Updated README to make clustering approach for 3D vs 2D clear #21 * Added DOI and citing info * Contributors: Artur Sagitov, Mohamed Zahran, Praveen Palanisamy 1.0.2 (2019-12-01) ------------------ * Added link to wiki pages * Updated readme with suuported pointcloud sources * Updated README to clarify real, sim, dataset LiDAR data * Contributors: Praveen Palanisamy 1.0.1 (2019-04-26) ------------------ * Fixed cv_bridge build depend * Removed indirection op to be compatible with OpenCV 3+ * Added visualization_msgs & cv_bridge build & run dependencies * Contributors: Praveen Palanisamy 1.0.0 (2019-04-13) ------------------ * Updated README with usage instructions * Renamed node name to kf_tracker to match bin name * Changed package name to multi_object_tracking_lidar * Updated package info & version num * Updated with a short demo on sample AV LIDAR scans * Added README with a short summary of the code * Working state of Multiple object stable tracking using Lidar scans with an extended Kalman Filter (rosrun kf_tracker tracker). A naive tracker is implemented in main_naive.cpp for comparison (rosrun kf_tracker naive_tracker). * v2. Unsupervised clustering is incorporated into the same node (tracker). * v1. Object ID/data association works. In this version PCL based unsupervised clustering is done separately. * Contributors: Praveen Palanisamy