MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202641096089 A) filed by Snehal Dileep Guruphale; Dr. K Sailaja Kumar; Dinesh Kumar Yadav; S. V. Saveeithaa; Dr. P Agilan; K. Amarnnath; Avani Anawardekar; T Gobi; Dr. Pendurthy Anthony Sunny Dayal; Dasari Somasekhar; Dr. Ranjitsinh Subhash Pawar; and Dr. A. Selvaraj on August 08, 2026, for Machine Learning-Based Adaptive Nonlinear Control Device For Intelligent Drone Swarm Communication Over 6g Networks.
Inventors include Snehal Dileep Guruphale; Dr. K Sailaja Kumar; Dinesh Kumar Yadav; S. V. Saveeithaa; Dr. P Agilan; K. Amarnnath; Avani Anawardekar; T Gobi; Dr. Pendurthy Anthony Sunny Dayal; Dasari Somasekhar; Dr. Ranjitsinh Subhash Pawar; and Dr. A. Selvaraj.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: The current invention presents a Machine Learning-Based Adaptive Nonlinear Control Device for Intelligent Drone Swarm Communication over 6G Networks, which amalgamates Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), adaptive nonlinear control, swarm intelligence, edge computing, and sixth-generation (6G) wireless communication technologies to facilitate autonomous coordination and intelligent communication among multiple unmanned aerial vehicles (UAVs). The gadget persistently gathers real-time flight characteristics, sensor data, ambient information, communication quality metrics, and mission-related data from drones functioning within a swarm. A data preprocessing and sensor fusion module produces dependable inputs for a hybrid machine learning prediction engine utilising Deep Neural Networks (DNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Graph Neural Networks (GNN), Federated Learning, Reinforcement Learning, and Ensemble Learning algorithms to forecast flight dynamics, enhance swarm formation, communication efficacy, trajectory planning, and energy efficiency. A nonlinear adaptive control module dynamically manages flight stability, synchronisation, navigation, and collaborative task performance in response to varying environmental variables. The invention additionally integrates intelligent 6G communication management, collision avoidance, autonomous mission planning, energy optimisation, cybersecurity, and Explainable Artificial Intelligence (XAI) to ensure secure, dependable, transparent, and low- latency operations of drone swarms. The proposed system, built on a scalable cloud-edge computing architecture, markedly enhances communication reliability, flight stability, operational efficiency, resource utilisation, and autonomous decision-making, rendering it appropriate for applications such as disaster response, surveillance, logistics, smart agriculture, environmental monitoring, military operations, infrastructure inspection, and smart city services.
Disclaimer: Curated by HT Syndication.
