A Novel Perspective for Source Localization in Underwater Active Electrosense Robots Based on Sparse Signal Reconstruction

Weakly electric fish can detect and localize objects in dark and turbid environments by sensing the perturbations induced by objects in their self-generated electric field. Massive efforts have been made to develop active electrosense systems for underwater robots that can rival those of fish. However, a well-performed localization method is always a challenge for underwater active electrosense robots. In this paper, we investigated the underwater active electrolocation problem from the novel perspective of sparse signal reconstruction. The source localization problem is formulated as a sparse signal recovery problem. The weighted matrix is designed to enhance the sparsity, and a multi-resolution grid search strategy is introduced to reduce the computational complexity. Experiments were conducted on a carefully designed underwater robot prototype. The results validate the proposed method's effectiveness and superiority over the existing works. Our work provides a promising and robust method to meet the precise localization needs of underwater small objects for robots in turbid and cramped environments.