Haircutting robots: a mobile robotics perspective

The development of haircutting robots has gained increasing attention in personal grooming and healthcare applications. However, existing research remains fragmented, often addressing perception, hair modelling, and motion planning in isolation and lacking a unifying theoretical foundation. To bridge this gap, this review examines robotic haircutting from the perspective of mobile robotics, highlighting the shared principles of localisation, coverage planning, and control. Specifically, localisation establishes the spatial relationship between the cutting tool and the human head; coverage planning formulates trimming as a multi-pass path coverage problem under safety and aesthetic constraints; and control strategies support compliant, efficient, and personalised execution. Furthermore, learning-based approaches and techniques from autonomous systems are discussed as important enablers of adaptability and robustness. By mapping the conceptual and methodological connections between mobile robotics and haircutting robots, this paper provides a structured synthesis of current research and proposes a unified framework to guide future studies in this emerging field.