Unmanned autonomous systems have gone through successful developments. They are widely applied in complex environments, including unmanned vehicles, unmanned aerial vehicles, service robots, space robots, marine robots and unmanned/intelligent plants.

However, unmanned autonomous systems have to deal with a complex operation environment. An unknown environment model, high spatiotemporal complexity, rapid changes of light intensity, and unknown disturbances arising from the dynamic environments often lead to the rapidly increasing complexity of the control algorithm, which then results in difficulties for the real-time controllers of unmanned autonomous systems. In addition, with the advent of sensing technology, providing the real-time environment information for unmanned autonomous systems through sensing the complex environment is another challenge. Therefore, revealing the properties and behaviours of unmanned autonomous systems working in complex environments could provide not only novel learning and control algorithms, but could also provide solutions for systems operating realistically and efficiently in complex and unmodelled scenarios.

This Special Issue will present advances in control theories and their potential engineering applications for unmanned autonomous systems in complex environments and provide a comprehensive overview of future solutions from various computational and engineering aspects. Authors are invited to present mathematical theories, algorithms, frameworks, experiments, and applications aiming at bringing about advanced sensing, learning and control techniques for unmanned autonomous systems working within complex and unpredictable behaviours such as structural uncertainties, unknown nonlinearities, time-vary delays, unknown external disturbances, unpredictable human motions, and uncertain system dynamics. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Learning and control of unmanned autonomous systems
• Learning complex manipulation
• Computational architectures and models for unmanned autonomous systems
• Hierarchical control of unmanned autonomous systems
• Advanced sensing in complex environment
• Disturbance-observer based control in complex environments
• Optimization in complex environment
• Intelligent planning and decision-making for unmanned autonomous systems
• Human-in-the-loop for complex manipulation
• Applications of unmanned autonomous systems