A Survey on Soft Robot Adaptability: Implementations, Applications, and Prospects
Zixi Chen, Di Wu, Qinghua Guan, David Hardman, Federico Renda, Josie Hughes, Thomas George Thuruthel, Cosimo Della Santina, Barbara Mazzolai, Huichan Zhao, Cesare Stefanini
AI summary
Problem
Soft robotics research is expanding rapidly, but adaptability—a core advantage—is often studied in isolation across hardware, sensing, and control, lacking a cohesive taxonomy to guide future development.
Approach
The authors systematically categorize adaptability into external and internal types, then review advancements in compliant design, sensing, and control strategies while mapping them to practical applications and future challenges.
Key results
- Classifies adaptability into external (passive/active) and internal (robust/transferable) frameworks
- Reviews spatial, temporal, and dynamic compliance regulation strategies for hardware design
- Evaluates sensing architectures and adaptive algorithms for proprioception and exteroception
- Maps adaptability advancements to key applications including surgery, wearables, locomotion, and manipulation
Why it matters
Provides researchers and engineers with a unified taxonomy and roadmap to accelerate the development of reliable, versatile soft robots for healthcare, industrial, and field applications.
Abstract
Soft robots, compared to rigid robots, possess inher- ent advantages, including higher degrees of freedom, compliance, and enhanced safety, which have contributed to their increasing application across various fields. Among these benefits, adapt- ability is particularly noteworthy. In this paper, adaptability in soft robots is categorized into external and internal adaptability. External adaptability refers to the robot’s ability to adjust, either passively or actively, to variations in environments, object properties, geometries, and task dynamics. Internal adaptability refers to the robot’s ability to cope with internal variations, such as manufacturing tolerances or material aging, and to generalize control strategies across different robots. As the field of soft robotics continues to evolve, the significance of adaptability has become increasingly pronounced. In this review, we summarize various approaches to enhancing the adaptability of soft robots, including design, sensing, and control strategies. Additionally, we assess the impact of adaptability on applications such as surgery, wearable devices, locomotion, and manipulation. We also discuss the limitations of soft robotics adaptability and prospective directions for future research. By analyzing adaptability through the lenses of implementation, application, and challenges, this paper aims to provide a comprehensive understanding of this essential characteristic in soft robotics and its implications for diverse applications.