Sensor Fusion for Autonomous Drone Waypoint Navigation Using ROS and Numerical P Systems: A Critical Analysis of Its Advantages and Limitations

Membrane computing (or P systems) is already a mature area of natural computing, inspired by the architecture and functioning of biological cells. Numerous theoretical results and application studies have demonstrated the power of P systems as distributed and parallel computing models. In this regard, there has been an increasing interest lately in the application of membrane computing in robotics. This has led to the introduction of new theoretical models of membrane systems (e.g. enzymatic numerical P systems) and the design of novel ways to control robots and swarms of robots using membrane systems. The problem addressed in this paper is sensor fusion for autonomous drone waypoint navigation, and a solution based on numerical P systems and Robot Operating System (ROS, a widely used software framework for building robotic systems) is developed and presented here. A critical analysis of the results offers new insights into the advantages and limitations of the use of membrane computing in controlling robots and drones.