Robotic Haircutting Systems: A Survey of Methods, Challenges, and Hair Modeling Insights

The field of robotic haircutting is rapidly evolving, merging advances in service robotics, computer vision, force sensing, and deep learning. This survey paper highlights the growing importance of robotic systems in personal grooming, driven by demographic shifts, technological innovation, and increasing demand for hygienic, consistent services. We review the historical evolution of robotic haircutting technologies, including DIY solutions, academic prototypes, and emerging commercial systems. Core technologies such as robotic arms, hair modeling, motion planning, and tactile sensing are discussed in detail. Key challenges including hair variability, real-time decision-making, user customization, and safety considerations are analyzed. Furthermore, we explore the transformative role of virtual hairstyle modeling and the integration of multimodal perception and AI-driven personalization. Future research directions emphasize the incorporation of large language models, vision-language models, reinforcement learning, and diffusion models to advance human-robot collaboration in salons, while addressing ethical, societal, and inclusivity considerations.