Fault-Tolerant Strategies for Intelligent Soft Robotic Systems: Design and Control Perspectives

Dear Colleagues,

Soft robotic systems have emerged as a transformative technology, offering safe, adaptable, and highly flexible operations ranging from biomedical devices and wearable exoskeletons to autonomous drones and aerospace manipulators. However, their inherent compliance and complex material properties introduce unique challenges in sensing, actuation, and control. Operating these systems in mission-critical environments further demands robust strategies to ensure reliability and safety under uncertain and dynamic conditions.

Faults are inevitable in advanced engineering systems, arising from hardware malfunctions, sensor inaccuracies, external disturbances, or unpredictable environmental interactions. In soft robotics, such risks are amplified by flexible materials and intricate actuation mechanisms, which can render traditional control schemes insufficient when dealing with faults. As soft robotics expands into safety-critical domains—such as aerospace applications—the importance of robust fault tolerance becomes paramount. A single fault not only disrupts performance but may also endanger personnel, equipment, or overall mission success.

Consequently, the early integration of fault-tolerant strategies into soft robotic design and control is essential to maintain resilience, reliability, and operational continuity. Recent advances in artificial intelligence (AI) offer unprecedented opportunities to develop intelligent fault-tolerant control architectures. Such architectures must ensure system reliability, stability, and safety. By combining cutting-edge AI with innovative hardware and embedded systems, engineers can create solutions that predict and adapt to incipient faults, thereby enhancing overall robustness.

This Special Issue aims to collect and disseminate the latest research on the design, analysis, and implementation of fault-tolerant strategies in soft robotic systems, with a strong emphasis on aerospace applications and the integration of AI-driven methods for both design and control. By examining cutting-edge theoretical frameworks and real-world case studies, we underscore the interdisciplinary nature of fault tolerance in ensuring the reliability of next-generation robotics and autonomous systems. Particular focus is placed on fault-tolerant system design and control algorithms, as well as AI-based architectures that support soft robotic platforms—such as drones and satellites with soft actuators. These configurations enable adaptive fault detection, robust self-correction, and enhanced safety, even under challenging or unpredictable conditions.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• AI-driven fault detection and fault-tolerant control for soft robots;
• Integration of soft robotic systems with aerospace platforms;
• Design, fabrication, and advanced materials for fault-resilient soft robotic actuators, especially in aerospace environments;
• Modeling, simulation, and real-time validation frameworks tailored to aerospace conditions;
• AI algorithms for managing incipient faults under harsh conditions;
• Multi-agent and swarm-based fault tolerance strategies for distributed soft robotic systems;
• Safety, certification, and regulatory considerations for deploying soft robotics in aerospace applications;
• Fault tolerance architecture in aerospace applications with an intelligent method.

Dr. Mahya Ramezani
Prof. Dr. Holger Voos
Guest Editors

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• soft robotics
• intelligent fault-tolerant design and control
• fault tolerance architecture in aerospace applications
• AI-driven methods
• real-time fault detection
• path planning and navigation
• integration of soft robotics in aerospace
• autonomous fault-tolerant systems
• distributed soft robotic systems