By Or Tslil, Amit Elbaz
ROS implementation of online semantic SLAM, based on the a published paper - "Representing and updating object identities in semantic SLAM". The object detection node is based on SSD300 architecture and forked from https://github.com/balancap/SSD-Tensorflow.
The following python packges are required:
- python 2.*
- numpy
- sklearn
- sciPy
- openCV
- TensorFlow 1.1* (GPU version)
- hector_mapping (http://wiki.ros.org/hector_mapping)
- currently tested in ros melodic in ubuntu 18.04
- Download repository to your catkin workspace:
git clone https://github.com/or-tal-robotics/object_map.git
- Build:
catkin_make
- Install SSD image detector for ROS:
pip install -e object_detector_ssd_tf_ros
- Unzip SSD weights in
object_map/object_detector_ssd_tf_ros/ssd/model/ssd_300_vgg.ckpt.zip
- For a demo simulation use:
roslaunch gazebo_demo demo.launch
- For a demo simulation working with the "Bhattacharyya coefficient" method of updating the map use:
roslaunch gazebo_demo Test.launch