Touch at a distance : underwater object identification using pressure sensors

Abstract

While the vast majority of underwater vehicles rely exclusively on sonar and vision to detect obstacles and maneuver, live fish also use their lateral line organ. The role played by the canal lateral line system is particularly important for hypogean fish, such as blind Mexican cave fish, who use it to avoid obstacles and navigate dexterously in complex environments. Similarly, pressure sensors could be used on underwater vehicles to expand their range of operability by filling the gap left by sonar and vision systems in turbid cluttered environments. To understand how much information can be extracted from the artificial lateral line of an underwater vehicle exploring an unknown environment, the case of a foil passing a static object in still water is analyzed. A two-dimensional potential flow approach based on a source panels method is used to characterize the spatio-temporal pressure signature of the object as sensed by the vehicle. Simulations are used to estimate the sensing range of an artificial lateral line and the appropriate density of pressure sensors. To emulate the object-detection and shape-recognition capabilities of the lateral line, an adapted unscented Kalman filter is combined with the hydrodynamic model. The method developed is experimentally tested in a water tank, using a hydrofoil instrumented with pressure sensors passing a static cylinder. The results show that location and shape informations of an elliptical cylinder can be successfully inferred from experimental pressure measurements. Performance of the proposed method for object identification using pressure sensors are discussed and ways to improve it are suggested.