Robust Navigation under Compromised GPS

Purpose and goal:

Our goal is to develop a robust navigation system for drones, where GPS interference can jeopardize safety in critical operations. The system leverages AI to map landmarks via cameras and integrates course, altitude, and acceleration data to enhance positioning accuracy. Using multiple-hypothesis tracking (MHT), we can precisely predict the position even in disrupted environments. Optimized with MHT technology and advanced solutions, the system is well-suited for dynamic and demanding operation.

Expected results and effects:

Our system provides GPS-independent positioning solutions at low altitudes, which is crucial during interference. This technology supports robust navigation and safer airborne operations by ensuring accurate positioning for drones and low-flying vehicles. By combining sensor data fusion and AI, we enhance knowledge and capacity in advanced data integration and AI modeling, delivering long-term benefits to societal infrastructure and safety.

Approach and implementation: Data Collection (Nov-Jan) Acquisition of drones for data collection and fieldwork for data gathering. Algorithm Implementation (Feb-Aug) Set up infrastructure for data management. Train the ML algorithm with collected data and modify our MHT code. Algorithm Evaluation (Feb-Aug)

Test the algorithm with progressively new data and improve the implementation. Prepare for Commercialization (Jan-Aug) Documentation, marketing, and establishing relevant contacts.