Driving Methods of Soft Robots for Multi-Scenario Applications

Existing driving methods often face problems such as difficulty in precise control, slow response, high energy consumption, or limited operating range, making it difficult to meet the needs of multi-scenario applications. This paper focuses on the research of driving methods for soft robots, sorting out four typical driving methods: among fluid-driven methods, pneumatic drive is suitable for environment exploration, and hydraulic drive for minimally invasive surgery; in intelligent material-driven methods, shape memory alloys are used in telescopic mechanisms, and electroactive polymers in bionic robots and interaction scenarios; magnetic drive is adapted to clean environments; chemical reaction-driven methods can complete operations. Meanwhile, this paper analyzes the advantages and limitations of various drives, such as insufficient precise control of pneumatic and hydraulic drives, slow response and high energy consumption of shape memory alloys, strict requirements for magnetic control in magnetic drive, and difficulty in controlling the process of chemical reaction-driven methods. The research points out that efforts need to develop new driving strategies through interdisciplinary integration of materials science, control science, etc., to improve driving efficiency, accuracy, and environmental adaptability. This paper provides a reference for researchers in soft robot driving, helping to promote the commercialization of soft robots in multi-scenario applications.