Intellectual Property India Publishes Patent Application for 'Lidar Based Self Driving Car Object Detection For Military Spying' Filed by Srinivasa Ramanujan Institute Of Technology; Y. Rajakullayi Reddy; P. Vamsidhar; G. Uday Kumar; and K. Sai

MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641051523 A) filed by Srinivasa Ramanujan Institute Of Technology; Y. Rajakullayi Reddy; P. Vamsidhar; G. Uday Kumar; and K. Sai, Ananthapuramu, Andhra Pradesh, on April 22, for 'lidar based self driving car object detection for military spying.'

Inventor(s) include Srinivasa Ramanujan Institute Technology; Y. Rajakullayi Reddy; P. Vamsidhar; G. Uday Kumar; and K. Sai.

The application for the patent was published on May 1, under issue no. 18/2026.

According to the abstract released by the Intellectual Property India: "This project presents a compact LIDAR-based autonomous ground vehicle designed for long-range object detection and situational awareness. A Raspberry Pi running vision software controls a USB camera and processes image-based object recognition; when the onboard LIDAR (Luna LIDAR) detects an obstacle or a region of interest, the system triggers higher-fidelity sensing and targeted camera capture. Low-level motion control (wheel motors, steering) is handled by an Arduino interfaced with a motor driver; a 12 V battery and a power-splitting distribution network supply the platform and peripherals. A pan/tilt servo rotates the LIDAR to build a 2 D scan sweep for left/right localization, while environmental conditions (temperature) are monitored by a DHT11 sensor to support robust operation in varied climates. Sensor fusion between LIDAR range data and camera detections enables the vehicle to differentiate obstacles from objects of interest and to make simple autonomous decisions (stop, skirt, approach, or re-route) in real time. The architecture emphasizes modularity (separate perception and control nodes), low cost, and on-board processing to minimize communications overhead. Experimental results on a prototype demonstrate reliable obstacle detection and basic target acquisition in cluttered environments, showing the platform's potential for remote reconnaissance and automated monitoring applications."

Disclaimer: Curated by HT Syndication.