MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202621100538 A) filed by Dr. D. Y. Patil Institute Of Technology, Pimpri, Pune on August 20, 2026, for Navigo: Smart Assistance For The Visually Impaired.
Inventors include Dr. Vikas Singh Panwar; Mr. Dhruv Kumbhar; Mr. Vedant Kumbharkar; Mr. Vinayak Karale; Ms. Saniya Mundhe; Ms. Deeksha Tomar; and Dr. Vikash K. Agrawal.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: The system integrates advanced computer vision, artificial intelligence, and sensor fusion technologies to provide accurate environmental perception and real-time feedback to the user. At its core, Navigo utilizes a deep learning-based object detection algorithm (YOLOv5) optimized for embedded systems, which enables rapid and precise identification of various obstacles in both indoor and outdoor environments. The device is equipped with a combination of LiDAR sensor, and an Inertial Measurement Unit (IMU), enabling robust spatial awareness, obstacle avoidance and localization. These sensor inputs are processed locally using a Raspberry Pi 4B computing module, eliminating the need for cloud-based computation and ensuring full offline operability. The identified obstacles are communicated to the user via real-time audio instructions through voice prompts. This multimodal communication enables the user to perceive spatial cues intuitively and respond promptly to dynamic environmental changes. In addition to real-time detection and avoidance, Navigo introduces a novel preliminary mapping feature that simulates local route planning to optimize navigation in unfamiliar environments. The device is built with an ergonomic, lightweight telescopic structure supported by an omnidirectional wheel mechanism that provides enhanced stability and ease of movement across varied terrains. The design emphasizes user-centric features such as comfort, portability, and ease of operation, making it suitable for daily use. Navigo offers a significant improvement over existing solutions like traditional canes, guide dogs, and smartphone-based assistive apps, by addressing key limitations such as limited detection range, lack of dynamic feedback, and dependency on internet connectivity. Its modular and scalable architecture allows for future enhancements including GPS integration, personalized AI learning, and SLAM-based mapping. Overall, the invention presents a cost-effective, intelligent assistive device that empowers visually impaired individuals to navigate their surroundings with confidence, autonomy, and enhanced situational awareness.
Disclaimer: Curated by HT Syndication.
