The research area in Guidance, Navigation, and Control (GN&C) focuses on methods, algorithms, and architectures that enable autonomous vehicles—whether aerial, space, ground, or maritime—to determine their position, plan safe trajectories, and execute maneuvers with precision and robustness. The work integrates three fundamental pillars: navigation, which addresses state estimation and sensor fusion for localization and orientation; guidance, responsible for trajectory generation and mission planning strategies; and control, aimed at stabilization and trajectory tracking under uncertainties, disturbances, and actuator limitations.
An increasingly important aspect within GN&C research is energy efficiency. Developed methods seek to minimize energy consumption—whether electrical, chemical, or another form—through optimized trajectories, reduced control effort, and strategies that limit unnecessary actuation. This focus is essential for extending the autonomy of UAVs, mobile robots, nanosatellites, and other systems operating with restricted energy resources.
Activities span classical techniques such as Kalman filtering and optimal control, as well as modern approaches based on optimization, predictive control, machine learning, and robust estimation. The area also involves the integration of software, hardware, and embedded systems to ensure real-time performance.
Applications include unmanned aerial vehicles, space systems, ground and maritime robots, and advanced industrial platforms. Typical projects explore efficient trajectory planning, control under saturation, inertial and vision-based navigation, obstacle avoidance, and the development of simulators and experimental platforms.
This research area prepares specialists capable of designing high-performance, energy-efficient autonomous systems that meet current and future challenges in modern engineering.