Vertical Applications of Multi-modal Sensor Fusion: A Comparative Study of Medical Robots and Industrial Robots

Multimodal sensor fusion technology significantly improves the perception and decision-making capabilities of medical and industrial robots by integrating multi-source information such as vision, touch, and mechanics. This article conducts a comparative analysis of the divergent applications and shared characteristics within two predominant domains: medical robotics, which emphasizes surgical safety and employs tactile-visual collaborative technologies to enhance operational precision while addressing data compliance challenges through a privacy protection framework; and industrial robotics, which prioritizes efficiency and safety in dynamic environments by integrating dynamic vision systems and high-precision ranging devices to facilitate real-time obstacle avoidance and fault diagnosis. The study found that although the scene goals are different (medical focuses on biocompatibility, industry focuses on cost efficiency), both face challenges such as sensor redundancy, data heterogeneity, and long-term stability. In the future, it is necessary to promote cross-domain technology interoperability, develop a lightweight adaptive fusion framework, and build an ethical and standardization system to promote the universalization and large-scale application of multimodal fusion technology.