ABSTRACT Achieving accurate reconstruction of spatial pressure distributions remains a challenge for flexible robotic sensor arrays due to issues such as signal crosstalk and spatial ambiguity. This study presents a flexible sensor array based on eutectic gallium‐indium (EGaIn) liquid metal microchannels, which enables high‐fidelity shape reconstruction through a combined theoretical and algorithmic framework. We establish a resistance‐sum model integrated with a bipartite graph mapping to theoretically analyze and guarantee uniqueness in pressure localization. Experimental and simulation results demonstrate that single‐point and continuous multi‐point pressures can be uniquely localized, whereas discrete distributions may exhibit ambiguity when pressure points lack row or column continuity, such as in cross‐row or cross‐column patterns, due to multiple equivalent edge sets in the bipartite graph. Furthermore, we develop a threshold‐based reconstruction method that significantly enhances the restoration of complex morphologies, including squares, square rings, and circles. This work provides a robust foundation for high‐fidelity shape reconstruction in flexible tactile sensing practices.
Zhang et al. (2026) studied this question.