MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202641100415 A) filed by Muneshwara M S; Prof. Arunkumar K L; Prof. H S Poornima Gowda; Prof. Priyanka A; Prof. Dhana Prasad R; Dr. Shivakumara T; and Prof. Amaresha K on August 19, 2026, for Ai-Integrated Autonomous Telescope With Real-Time Celestial Navigation And Observation.
Inventors include Muneshwara M S; Prof. Arunkumar K L; Prof. H S Poornima Gowda; Prof. Priyanka A; Prof. Dhana Prasad R; Dr. Shivakumara T; and Prof. Amaresha K.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: The present invention relates to an Artificial Intelligence (AI) integrated autonomous telescope system employing an adaptive astronomical knowledge graph and Graph Retrieval-Augmented Generation (Graph RAG) for real-time celestial navigation, intelligent observation planning, and autonomous telescope control. The system comprises an optical telescope, motorized positioning assembly, astronomical imaging module, environmental sensing unit, processing unit, memory, communication interface, and an adaptive decision engine. The processing unit executes computer vision algorithms to detect and classify celestial objects from acquired astronomical images. A dynamic astronomical knowledge graph continuously integrates information from astronomical catalogues, planetary ephemerides, telescope calibration records, atmospheric conditions, historical observation data, and real-time sensor measurements. A Graph RAG engine retrieves contextually relevant graph relationships associated with detected celestial objects and fuses the retrieved knowledge with live observational data. An adaptive learning engine continuously updates graph relationships and decision parameters based on observation quality metrics, environmental variations, tracking accuracy, image acquisition performance, and historical observation outcomes. A closed-loop autonomous decision engine utilizes the dynamically updated graph knowledge to determine telescope orientation, optimize tracking trajectories, configure exposure parameters, schedule observation sequences, initiate adaptive recalibration, and autonomously modify observation strategies in response to changing environmental conditions. The system further generates contextual scientific observation reports based on the retrieved graph knowledge and acquired astronomical data. The disclosed invention provides an adaptive self-learning autonomous telescope capable of continuously improving celestial navigation, observation planning, telescope control, and scientific documentation with minimal human intervention.
Disclaimer: Curated by HT Syndication.
