Research progress and prospect of sensor-based automatic sewing technologies for garment intelligent manufacturing

Garment manufacturing is a labor-intensive industry facing challenges of high labor intensity and inconsistent product quality. Automatic sewing technology, as a core direction of intelligent upgrading, has attracted extensive research attention in recent years. This review summarizes the latest progress of automatic sewing control methods based on different sensor information in garment processing. First, it analyzes the inherent difficulties of garment automation caused by the soft and deformable characteristics of fabrics. Then, it systematically elaborates on three categories of control methods: force feedback-based, visual feedback-based, and multi-sensor information fusion-based sewing methods, including their technical principles, research progress, applicable scenarios, advantages, and limitations. Finally, it discusses the current application status of related technologies and prospects three key future research directions: 3D automatic sewing for soft materials, online quality control during sewing, and multi-degree-of-freedom adaptive feeding structures. This review provides a comprehensive reference for the development and application of intelligent sewing technology in the garment manufacturing industry.