We develop a framework to build a semantic map based on radio quality. By means of our proposed approach, mobile robots can gain knowledge on up-to-date radio context map information of the surrounding environment, hence enabling reliable and efficient robotics operations. As a result, we design and implement a robotic software package that allows the robot to create semantic maps that can later be translated into occupancy grid maps merged with the main map topic (from your SLAM algorithm). Semantic interpretations are easy to configure as a list of colors to be considered “virtual” obstacles in the new map. I.E Low quality area of radio 5G signal. This in term will make the ROS2 nav2 package avoid the blind spots. This application is very useful for cloud based mobile robots that offload computational resources to the cloud and want to keep QoS and QoE specific metrics.

Software and preliminary results are made public to foster research on this topic, and can be found online on 5GERA Github page (https://github.com/5G-ERA).