Object Analytics (OA) is ROS2 wrapper for realtime object detection, localization and tracking. These packages aim to provide real-time object analyses over RGB-D camera inputs, enabling ROS developers to easily create amazing robotics advanced features, like intelligent collision avoidance and semantic SLAM. It consumes sensor_msgs::PointClould2 data delivered by RGB-D camera, publishing topics on object detection, object tracking, and object localization in 3D camera coordination system.
OA keeps integrating with various “state-of-the-art” algorithms. By default, backend of object detection is Intel® movidius ncs2.
2. Running the demo¶
Object Analytics with OpenVINO toolkit
# In terminal 1: source environment and launch realsense backend source /opt/robot_devkit/robot_devkit_setup.bash ros2 run realsense_node realsense_node # In terminal 2: launch openvino backend source /opt/robot_devkit/robot_devkit_setup.bash export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/intel/openvino/deployment_tools/inference_engine/samples/build/intel64/Release/lib . /opt/intel/openvino/bin/setupvars.sh ros2 launch dynamic_vino_sample ros2_openvino_oa.launch.py # In terminal 3: launch object analytics source /opt/robot_devkit/robot_devkit_setup.bash ros2 launch object_analytics_node object_analytics_sample.launch.py
OA demo video:
By default, object analytics will launch both tracking and localization features, but either tracking or localization or both can be dropped. Detailed please refer comments embedded in launch file.
4. Known issues¶