Special Issue: Advancements in Safety-Critical Control for Autonomous Intelligent Systems

In recent years, the rapid advancements in artificial intelligence (AI), robotics, and automation technologies have led to the emergence of intelligent automation systems with unprecedented capabilities. These systems, including automated storage and retrieval systems, self-driving vehicles, and various types of autonomous robots, have the potential to revolutionize industries and everyday life. However, the autonomous operation of these systems introduces new challenges, particularly in ensuring their safety and reliability, which are crucial for their widespread adoption and acceptance.

The aim of this special issue is to address these challenges by focusing on "Advancements in Safety-Critical Control for Autonomous Intelligent Systems." The primary motivation behind this special issue is to provide a platform for researchers and practitioners to share insights, methodologies, and innovative solutions aimed at enhancing the safety and reliability of intelligent automation systems. By bringing together experts from the fields of control, robotics, and AI, this special issue seeks to advance the state-of-the-art in safety-critical control and contribute to the development of safer and more reliable autonomous systems.

The topics of interest within the scope of this Special Issue include (but are not limited to) the following:

• Intelligent fault detection and fault-tolerant control of intelligent automation systems.

• Reliability and traceability of decision-making for intelligent automation systems.

• Risk assessment of artificial intelligence (AI)-based automation systems.

• Model-based safety and cybersecurity assessment of intelligent automation system.

• Ethical framework for designing automation systems.

• Interests and risks of learning-based control.

• Conflict detection and resolution of intelligent automation systems.

• Safety- and security-related issues.

• Functional safety and system security in automation systems

• Human-robot collaboration-Risk assessment of intelligent automation

• Design, development, validation, and applications of intelligent automation systems (e.g., unmanned ground vehicles (UGV), unmanned aerial vehicles (UAV), unmanned underwater vehicles (UUV)).