Real Time Navigation

Real-time navigation research focuses on enabling robots and autonomous systems to navigate dynamically changing environments safely and efficiently. Current efforts concentrate on integrating diverse sensor data (LiDAR, cameras, IMUs, GNSS) using advanced algorithms like Kalman filters, Gaussian processes, and model predictive control, often within frameworks incorporating information-rich map representations such as Gaussian splatting and neural potential fields. These advancements are crucial for improving the robustness and reliability of autonomous systems in various applications, ranging from indoor robotics and autonomous driving to assistive technologies for people with visual impairments.