Robotics and autonomous systems

The research on robotics and autonomous systems spans a broad range of applications, including mechanical and Lagrangian systems, industrial and service robotics, marine craft, aircraft, uncrewed vehicles, satellites, compressors, automotive systems, and integrated navigation and sensor fusion platforms.

Core research areas include nonlinear control theory, optimization, parameter estimation, Kalman filtering, nonlinear observers, state estimation, mission and path planning, robot perception, simultaneous localization and mapping (SLAM), robotic vision, machine learning, reinforcement learning (RL), artificial intelligence (AI), and deep policy learning.

Applications

• Guidance, navigation and control of marine craft, aircraft and drones
• Uncrewed vehicles (aerial, surface, and underwater)
• Robotics and robotic vision
• Integrated navigation systems and sensor fusion
• Automotive systems
• Control allocation
• Power and propulsion systems
• Spacecraft and satellite control systems
• Compressor control systems
• Machine learning and AI for autonomous decision-making and control
• Intelligent sensing, perception, and adaptive systems