Bio-inspired unified model for representing geometric relations in robotic perception

Despite remarkable progress in robotic visual technologies over the past decade, the modeling of complex geometric relations is still constrained by numerical models. These approaches exhibit inherent limitations in handling robotic visual contact perception, as dynamic interaction instantaneity and representation inconsistency diminish reliable comprehension of contact relationships. This paper presents a unified geometric model grounded in vector set operations, which establishes a mathematical equivalence between biological visual perception paradigms and robotic visual models. The proposed model facilitates continuous contact description without geometric discretization, which enables rapid characterization of complex contact states during dynamic interactions and provides a novel theoretical framework for robotic visual perception. This innovation is further reinforced by its engineering implementation as a mathematical framework that integrates the principles of biological vision, significantly enhancing the ability to interpret and interact with the complex physical environments of advanced robotic systems.