Model based object localization and shape estimation using electric sense on underwater robots

An Improved Underwater Electric Field-Based Target Localization Combining Subspace Scanning Algorithm And Meta-EP PSO Algorithm

In this paper, we propose an improved three-dimensional underwater electric field-based target localization method. This method combines the subspace scanning algorithm and the meta evolutionary programming (meta-EP) particle swarm optimization (PSO) algorithm. The subspace scanning algorithm is applied as the evaluation function of the electric field-based underwater target locating problem. The meta-EP PSO method is used to select M elite particles by the q-tournament selection method, which could effectively reduce the computational complexity of the three-dimensional underwater target localization. Moreover, the proposed meta-EP PSO optimization algorithm can avoid subspace scanning trapping into local minima. We also analyze the positioning performance of the uniform circular and cross-shaped electrodes arrays by using the subspace scanning algorithm combined with meta–EP PSO. According to the simulation, the calculation amount of the proposed algorithm is greatly reduced. Moreover, the positioning accuracy is effectively improved without changing the positioning accuracy and search speed.

Representation of object's shape by multiple electric images in electrolocation

Weakly electric fish generate an electric field by discharging an electric organ located on the tail region. An object near the fish modulates the self-generated electric field. The modulated field enables the fish to perceive objects even in complete darkness. The ability to perceive objects is provided by the electrosensory system of the fish. Electroreceptors distributed on the fish's skin surface can sense the modulated field, on the basis of transdermal voltage across the skin surface, called electric images. The fish can extract object's features such as lateral distance, size, shape, and electric property from an electric image. Although previous studies have demonstrated the relationship between electric-image features and object's distance and size, it remains unclear what features of an electric image represent the object's shape. We make here a hypothesis that shape information is not represented by a single image but by multiple images caused by the object's rotation or fish movement around the object. To test the hypothesis, we develop a computational model that can predict electric images produced by the rotation of differently shaped objects. We used five different shapes of resistive objects: a circle, a square, an equilateral triangle, a rectangle, and an ellipsoid. We show that differently shaped objects of a fixed arrangement generate similar Gaussian electric images, irrespective of their shapes. We also show that the features of an electric image such as the peak amplitude, half-maximum width, and peak position exhibit the angle-dependent variations characteristic to object rotation, depending on object shapes and lateral distances. Furthermore, we demonstrate that an integration effect of the peak amplitude and half-maximum width could be an invariant measure of object shape. These results suggest that the fish could perceive an object shape by combining those image features produced during exploratory behaviors around the object.

A bio-inspired electric camera for short-range object inspection in murky waters

Underwater object inspection by optical sensors is usually unreliable in turbid or dark environments. Here, we designed a biomimetic 'electric camera', inspired by weakly electric fish Gnathonemus petersii, which successfully use active electrolocation for this task. The device probed nearby objects with a weak electric field and captured 'electric images' of the targets by processing the object-evoked field modulations. The camera-based electric images strongly resembled those available to G. petersii. Furthermore, by extracting the fish's analytical cues from these images, close objects could be reliably analysed. Based on the level of 'image blurring' short distances of electrolocation targets, spheres of different sizes and material were estimated. Natural targets, fish or plants, were identified irrespective of their size or distance by their two individual 'electric colours' derived from electric images. Furthermore, we introduce an image cue, called the 'electric outline', which provided information resembling a target's optical contour. Our results indicate that bio-inspired electric imaging principles provide promising cues for sensor-based, short-range object inspections in murky waters. By resembling the electric imaging applied by G. petersii our device can also be used for 'reverse biomimetics', revealing imaging cues that so far have not been considered for weakly electric fish.

Active Electro-Location of Objects in the Underwater Environment Based on the Mixed Polarization Multiple Signal Classification Algorithm

This article proposes a novel active localization method based on the mixed polarization multiple signal classification (MP-MUSIC) algorithm for positioning a metal target or an insulator target in the underwater environment by using a uniform circular antenna (UCA). The boundary element method (BEM) is introduced to analyze the boundary of the target by use of a matrix equation. In this method, an electric dipole source as a part of the locating system is set perpendicularly to the plane of the UCA. As a result, the UCA can only receive the induction field of the target. The potential of each electrode of the UCA is used as spatial-temporal localization data, and it does not need to obtain the field component in each direction compared with the conventional fields-based localization method, which can be easily implemented in practical engineering applications. A simulation model and a physical experiment are constructed. The simulation and the experiment results provide accurate positioning performance, with the help of verifying the effectiveness of the proposed localization method in underwater target locating.