Research in location update schemes for geographical routing in Mobile Ad Hoc Networks (MANETs) focuses on improving the accuracy, scalability, and efficiency of location information dissemination among mobile nodes. Recent studies propose adaptive and mobility-aware update mechanisms that adjust the frequency of location updates based on node movement speed, direction, and network density to reduce control overhead. Prediction-based and machine learning–driven models are increasingly utilized to estimate future node positions, minimizing unnecessary broadcasts while maintaining routing accuracy. Energy-efficient and privacy-preserving update schemes are also being developed to safeguard location data and extend network lifetime. These advancements enhance route reliability, reduce communication cost, and improve the overall performance of geographic routing protocols in dynamic MANET environments.