A Context-Aware Finite State Machine for Gesture-Driven UAV Control
finite state machine; gesture recognition; MediaPipe; PX4; rOS2; UAV
Gesture based Unmanned Aerial Vehicles (UAVs) is a very intuitive way to control drones (UAVs). Current methods tend to associate one gesture to one action, a practice which is rigid and inflexible. In this paper, we propose the Finite State Machine (FSM)-based gesture control framework, which allows triggering several actions of the UAV with a single gesture depending on the current state of the drone. MediaPipe hand gestures recognition and integration with ROS2 and PX4 allows the system to automatically takeoff, land, hover, automated ascents, and directional speed variation. Experiments in a ROS2 simulation environment test the system in terms of gesture-to-state latency, the rate of successful commands, the extent of the FSM that the system is capable of controlling, and the rate of false positives (spurious transitions). The results indicate that the suggested method has robust and responsive control of the UAV, which forms the basis to establish more intuitive and adaptive human-UAV interaction in limited spaces. 2025 IEEE.
Pal Pandian, P.; Thomas Antony, M.; Ranoy Robert, M.
Proceedings of the 2025 International Conference on Computational Innovations and Sustainable Technologies, ICCIST 2025;
Institute of Electrical and Electronics Engineers Inc.
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1109/ICCIST67338.2025.11438537 https://www.scopus.com/pages/publications/105037470692?origin=resultslist
Pal Pandian P., Christ University, School of Engineering and Technology, Department of Mechanical and Automobile Engineering, Bangalore, 560074, India; Thomas Antony M., Christ University, School of Engineering and Technology, Department of Mechanical and Automobile Engineering, Bangalore, 560074, India; Ranoy Robert M., Christ University, School of Engineering and Technology, Department of Mechanical and Automobile Engineering, Bangalore, 560074, India