Work

Soft robotics actuated by smart materials applied in rail maintenance: Review of intelligent control and sensor methods

Year: 2025

Type: article

Abstract: As a critical component of modern urban infrastructure, the safe and efficient operation of rail transit systems is essential for ensuring the smooth functioning of society. However, with the continuous expansion of rail networks, conventional rail maintenance robots are increasingly unable to meet the growing demands for higher efficiency, greater precision, and reduced operational costs. In recent years, advancements in smart materials have opened new avenues for the development of next-generation soft robots tailored for rail maintenance applications. These materials possess the ability to respond to external stimuli—such as temperature, light, electric, or magnetic fields—enabling the design of robots that can adaptively interact with complex environments and delicate structures. By embedding smart materials into soft robotic systems, it becomes possible to achieve safe, adaptive deformation and efficient task execution, which are particularly valuable in the dynamic and constrained settings of rail infrastructure. To explore the potential of intelligent soft robots in this domain, this paper reviews the current state of research on smart materials and their integration into the design and control of soft robots, with a specific focus on addressing the unique challenges of rail environments, such as vibration, dust, humidity, and safety-critical constraints. The discussion focuses on various categories of smart materials, their functional properties, and their practical applications in soft robotics. Additionally, recent advancements and innovative approaches are highlighted. The paper concludes by addressing the challenges and strategies associated with sensing and control mechanisms in soft robots embedded with smart materials, thereby laying a theoretical and technological foundation for the realization of intelligent rail maintenance robots.

Source: Autonomous Transportation Research

DOI: 10.1016/j.atres.2025.11.002

Authors: Qianyi Chen, Xinhai Zhou, Yuxuan Dai, Liang Guo, Jovana Jovanova

Institutions: Delft University of Technology, Southwest Jiaotong University

Language: English

Topic: Soft Robotics and Applications

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: