Weakly electric fish use a navigational technique called electrolocation to investigate their surroundings for predator, prey and obstacles. Obstacles and other global stimuli are perceived as perturbations to the fish's self-generated electric field, which provide relevant navigational cues to the fish. In this work a control strategy based on electrolocation for performing obstacle avoidance in electrically heterogeneous environments is presented and validated. The control strategy developed for a straight tunnel is shown to be robust to small variations in the tunnel width. This justifies its application to other heterogeneous corridor-like environments. Static output feedback control is shown to achieve the desired goal of reflexive obstacle avoidance in such environments in simulation and experimentation. The proposed approach is computationally inexpensive and readily implementable on a small scale underwater vehicle, making underwater autonomous navigation feasible in real-time.

Potential flow theory is used to derive velocity magnitude information for a) inclined flow past a stationary cylinder, b) moving cylinder inside a tunnel and c) moving cylinder inside a circular arena. Wide-Field Integration methods which are bioinspired techniques are used to extract relative states from the velocity magnitude signals for the above three situations. A linear controller using these relative states has been simulated to produce rheotaxis, wide-field obstacle avoidance, centering and wall following behavior. The approach is extended to a viscous inclined flow over an airfoil using an off-the-shelf CFD package where rheotaxis is again demonstrated using the same controller.