Shape recognition and classification in electro-sensing

This paper aims at advancing the field of electro-sensing. It exhibits the physical mechanism underlying shape perception for weakly electric fish. These fish orient themselves at night in complete darkness by employing their active electrolocation system. They generate a stable, high-frequency, weak electric field and perceive the transdermal potential modulations caused by a nearby target with different admittivity than the surrounding water. In this paper, we explain how weakly electric fish might identify and classify a target, knowing by advance that the latter belongs to a certain collection of shapes. Our model of the weakly electric fish relies on differential imaging, i.e., by forming an image from the perturbations of the field due to targets, and physics-based classification. The electric fish would first locate the target using a specific location search algorithm. Then it could extract, from the perturbations of the electric field, generalized (or high-order) polarization tensors of the target. Computing, from the extracted features, invariants under rigid motions and scaling yields shape descriptors. The weakly electric fish might classify a target by comparing its invariants with those of a set of learned shapes. On the other hand, when measurements are taken at multiple frequencies, the fish might exploit the shifts and use the spectral content of the generalized polarization tensors to dramatically improve the stability with respect to measurement noise of the classification procedure in electro-sensing. Surprisingly, it turns out that the first-order polarization tensor at multiple frequencies could be enough for the purpose of classification. A procedure to eliminate the background field in the case where the permittivity of the surrounding medium can be neglected, and hence improve further the stability of the classification process, is also discussed.Comment: 10 pages, 15 figure

Electrocommunication for weakly electric fish

This paper addresses the problem of the electro-communication for weakly electric fish. In particular we aim at sheding light on how the fish circumvent the jamming issue for both electro-communication and active electro-sensing. A real-time tracking algorithm is presented

First results on a sensor bio-inspired by electric fish

This article presents the first results of a work which aims at designing an active sensor inspired by the electric fish. Its interest is its potential for robotics underwater navigation and exploration tasks in conditions where vision and sonar would meet difficulty. It could also be used as a complementary omnidirectional, short range sense to vision and sonar. Combined with a well defined engine geometry, this sensor can be modeled analytically. In this article, we focus on a particular measurement mode where one electrode of the sensor acts as a current emitter and the others as current receivers. In spite of the high sensitivity required by electric sense, the first results show that we can obtain a detection range of the order of the sensor length, which suggests that this sensor principle could be used in future for robotics obstacle avoidance

Underwater robot navigation around a sphere using electrolocation sense and Kalman filter

International audienceThe aim of this paper is to perform the navigation of an underwater robot equipped with a sensor using the electric sense. The robot navigates in an unbounded environment in presence of spheres. This sensor is inspired of some species of electric fish. A model of this sensor composed of n spherical electrodes is established. The variations of the current due to the presence of the sphere is related to the model of Rasnow [3]. Unscented Kalman Filter is used to localize the robot with respect to the sphere and to estimate the size of the sphere. We show that bio-inspired motions improve the detection of the spheres. We illustrate the efficiency of the method in two cases: a two electrodes sensor and a four electrodes sensor

Design and Implementation of Bio-inspired Underwater Electrosense

Underwater electrosense, manipulating underwater electric field for sensing purpose, is a growing technology bio-inspired by weakly electric fish that can navigate in dark or cluttered water. We studied its theoretical foundations and developed sophisticated sensing algorithms including some first-introduced techniques such as discrete dipole approximation (DDA) and convolutional neural networks (CNN), which were tested and validated by simulation and a planar sensor prototype. This work pave a solid way to applications on practical underwater robots

Estimation of relative position and coordination of mobile underwater robotic platforms through electric sensing.

International audienceIn the context of underwater robotics, positioning and coordination of mobile agents can prove a challenging problem. To address this issue, we propose the use of electric sensing, with a technique inspired by weakly electric fishes. In particular, the approach relies on one or several of the agents applying an electric field to their environment. Using electric measures, others agents are able to reconstruct their relative position with respect to the emitter, over a range that is function of the geometry of the emitting agent and of the power applied to the environment. Efficacy of the technique is illustrated using a number of numerical examples. The approach is shown to allow coordination of unmanned underwater vehicles, including that of bio-inspired swimming robotic platforms

A Novel Localization System for Experimental Autonomous Underwater Vehicles

Localization is a classic and complex problem in the field of mobile robotics. It becomes particularly challenging in an aqueous environment because currents within the water can move the robot. A novel localization module and corresponding localization algorithm for experimental autonomous underwater vehicles is presented. Unlike other available positioning systems which require fixed hardware beacons, this custom built module relies only on information available from sensors on-board the vehicle and knowledge of its bounded domain. This allows the user to save valuable time which would otherwise be devoted to the setup and calibration of a beacon or sensor network. The module uses three orthogonal ultrasonic transducers to measure distances to the tank boundaries. Using the measured tri-axial orientation of the vehicle, the algorithm analytically determines the robot\u27s position within the domain in absolute coordinates. Certain vehicle states do not allow the position to be completely resolved by the algorithm alone. In this case, state estimation is used to estimate the robot position until its state is no longer indeterminate. The modular design of this system makes it ideal for application on underwater vehicles which operate in a bounded environment for research purposes. An experimental version of the module was constructed and tested in the WPI swimming pool and showed successful localization under normal conditions

Shape recognition and classification in electro-sensing

This paper aims at advancing the field of electro-sensing. It exhibits physical mechanisms underlying shape perception for weakly electric fish. These fish orient themselves at night in complete darkness by using their active electrolocation system. They generate a stable, relatively high-frequency, weak electric field and perceive the transdermal potential modulations caused by a nearby target with different electromagnetic properties than the surrounding water. The main result of this paper is a scheme that explains how weakly electric fish might identify and classify a target, knowing in advance that the latter belongs to a certain collection of shapes. The scheme is designed to recognize living biological organisms. It exploits the frequency dependence of the electromagnetic properties of living organisms, which comes from the capacitive effects generated by the cell membrane structure. When measurements are taken at multiple frequencies, the fish might use the spectral content of the perceived transdermal potential modulations to classify the living target. inverse conductivity problem | polarization tensor | shape classification I n the turbid rivers of Africa and South America, some species of fish generate a stable, relatively high-frequency (0.1-10 kHz), weakly electric (≤100 mV/cm) field that is not enough for defense against predators. In 1958, Lissmann and Machin (1) discovered that the emitted electrical signal is in fact used for active electro-sensing. The weakly electric fish have thousands of receptors at the surface of their skins. A nearby target with different admittivity than the surrounding water perturbs the transdermal potential induced by the electric organ discharge (2, 3). Targets with large permittivity cause appreciable phase shifts, which can be measured by receptors called T-type units (4). It is an important input for the fish, and thus it will be the central point in this paper for shape classification. Active electro-sensing has driven an increasing number of experimental, behavioral, biological, and computational studies since Lissmann and Machin's work (5-12). Behavioral experiments have shown that weakly electric fish are able to locate a target (12) and discriminate between targets with different shapes (13) or/and electric parameters (conductivity and permittivity) (14). The growing interest in electro-sensing could be explained not only by the curiosity of discovering a sixth sense, electric perception, that is not accessible by our own senses, but also by potential bio-inspired applications in underwater robotics. It is challenging to equip robots with electric perception and provide them, by mimicking weakly electric fish, with imaging and classification capabilities in dark or turbid environments Mathematically speaking, the problem is to locate the target and identify its shape and material parameters given the current distribution over the skin. Due to the fundamental ill-posedness of this imaging problem, it is very intriguing to see how much information weakly electric fish are able to recover. The electric field perturbation due to the target is a complicated highly nonlinear function of its shape, admittivity, and distance from the fish. Thus, understanding analytically this electric sensing is likely to give us insight in this regard (5-7, 9, 13, 18, 21). Although locating targets from the electric field perturbations induced on the skin of the fish is now understood (17, 22), identifying and classifying their shapes are considered to be some of the most challenging problems in electro-sensing. Although the neuroethology of these fish has been significantly advanced recently (see ref. 23 and references therein), the neural mechanisms encoding the shape of a target are far beyond the scope of our study. Rather, this work focuses on the physical feasibility of such a process, which was not explained before. In ref. 22, a rigorous model for the electro-location of a target around the fish was derived. Using the fact that the electric current produced by the electric organ is time harmonic with a known fundamental frequency, a space-frequency location search algorithm was introduced. Its robustness with respect to measurement noise and its sensitivity with respect to the number of frequencies, the number of sensors, and the distance to the target were illustrated. In the case of disk-and ellipse-shaped targets, the conductivity, the permittivity, and the size of the targets can be reconstructed separately from multifrequency measurements. Such measurements have been used successfully in transadmittance scanners of breast tumors (24-26). The main result of this paper is the presentation and analysis of a scheme that allows to recognize and classify targets from multifrequency measurements of the electric field perturbations induced by the targets. To explain how the shape information is encoded in measured data, we distinguish two cases: recognition of nonbiological targets and recognition of living organisms. Most of the nonbiological objects have very low permittivities, and therefore, their electromagnetic parameters are frequency independent. Living targets have frequency-dependent electromagnetic parameters because their cell membrane structures induce capacitive effects (27), and therefore it is possible to exploit the spectral content of the data. We will mostly focus our attention on the second situation, but we first explain the strategy for the first one. Our model in this paper of the weakly electric fish relies on differential imaging, i.e., by forming an image from the perturbations of the field due to the target. The method is based on the multipole expansion for the perturbations of the electric field induced by a nearby target in terms of the characteristic size of the target. The asymptotic expansion derived in refs. 22 and 28 generalizes Rasnow's equation (29) in two directions: (i) it is a higher-order approximation of the effect of a nearby target, and it is valid for an arbitrary shape and admittivity contrast; and (ii) it also takes into account the body of the fish. As was first shown in ref. 22, one can reduce the Significance Weakly electric fish orient themselves in complete darkness by using their active electrolocation system. They generate a weak electric field and perceive the transdermal potential modulations caused by a nearby target with different electromagnetic properties than the surrounding water. The main result of this paper is a scheme that explains how weakly electric fish might identify and classify living biological organisms. This scheme exploits the frequency dependence of the electromagnetic properties of living organisms, which comes from the capacitive effects generated by the cell membrane structure