Towards enhanced live visualization based on communication delay prediction for remote AGV operation

This paper presents the development progress of a methodology to enhance the dynamic visualization of remote Automated Guided Vehicles (AGVs) using open source frameworks as Gazebo and ROS. The approach is based on a deterministic path pre-calculated by edge computing, accessible for a 3D web visualization cloud platform. The trajectory displayed is verified by a live position streaming from the AGV and a predicted communication delay value. By succeeding on the methodology proposed, it is expected to enhance the fidelity of the 3D live representation for every trajectory executed dynamically and autonomously by AGVs in the shop floor, leaving behind an initial scenario with low visualization fidelity due non-deterministic behavior of long-distance communication channels (including wireless networks essential for AGVs). This work aims to have an impact on improving the user experience of remote web-based interfacing tools to visualize the behavior of cyber-physical systems in agile manufacturing.