Perception and Control Technology for Intelligent Autonomous Unmanned Systems

Autonomous uncrewed systems (AUS) are electromechanical systems capable of independently completing specific tasks. The development of artificial intelligence technology can enhance their performance, thereby forming intelligent autonomous uncrewed systems (iAUSs). iAUSs represent a multidisciplinary field that relies on advancements in big data, artificial intelligence, and other scientific and technological fields, aiming to develop intelligent, autonomous, and collaborative uncrewed systems with integrated task execution capabilities, motion planning, decision-making, and reasoning abilities. Currently, these technologies have shown diverse intelligent development characteristics. This Special Issue aims to explore the various technologies involved in iAUS, introduce the latest research progress, and promote information exchange.

Since its establishment, this Special Issue has invited nearly 20 academic papers for submission, receiving widespread attention from scholars in related fields. Thanks to the hard work of the journal editors, this Special Issue includes eight articles from several universities and research institutes, covering mapping, detection, tracking, and navigation control methods for uncrewed systems in multi-dynamic environments, such as robust attitude estimation and high-fidelity scene reconstruction in dynamic environments, fault detection of photovoltaic hotspots, construction and representation of digital environmental spaces, tree trunk detection, intelligent classification of cassava diseases, uncrewed vehicle collaborative tracking, trajectory tracking, and dual-arm collaborative control.