Weakly electric fish are capable of efficiently performing obstacle avoidance in dark and navigationally challenging aquatic environments using electrosensory information. This sensory modality enables extraction of relevant proximity information about surrounding obstacles by interpretation of perturbations induced to the fish’s self-generated electric field. In this paper, reflexive obstacle avoidance is demonstrated by extracting relative proximity information using spatial decompositions of the perturbation signal, also called an electric image. Electrostatics equations were formulated for mathematically expressing electric images due to a straight tunnel to the electric field generated with a planar electro-sensor model. These equations were further used to design a wide-field integration based static output feedback controller. The controller was implemented in quasi-static simulations for environments with complicated geometries modelled using finite element methods to demonstrate sense and avoid behaviours. The simulation results were confirmed by performing experiments using a computer operated gantry system in environments lined with either conductive or non-conductive objects acting as global stimuli to the field of the electro-sensor. The proposed approach is computationally inexpensive and readily implementable, making underwater autonomous navigation in real-time feasible.