Reactive underwater object inspection based on artificial electric sense

Implementation of Underwater Electric Field Communication Based on Direct Sequence Spread Spectrum (DSSS) and Binary Phase Shift Keying (BPSK) Modulation

Stable communication technologies in complex waters are a prerequisite for underwater operations. Underwater acoustic communication is susceptible to multipath interference, while underwater optical communication is susceptible to environmental impact. The underwater electric field communication established based on the weak electric fish perception mechanism is not susceptible to environmental interference, and the communication is stable. It is a new type of underwater communication technology. To address issues like short communication distances and high bit error rates in existing underwater electric field communication systems, this study focuses on underwater electric field communication systems based on direct sequence spread spectrum (DSSS) and binary phase shift keying (BPSK) modulation techniques. To verify the feasibility of the established spread spectrum electric field communication system, static communication experiments were carried out in a swimming pool using the DSSS-based system. The experimental results show that in fresh water with a conductivity of 739 μS/cm, the system can achieve underwater current electric field communication within a 11.2 m range with 10-6 bit errors. This paper validates the feasibility of DSSS BPSK in short-range underwater communication, and compact communication devices are expected to be deployed on underwater robots for underwater operations.

Scaling the tail beat frequency and swimming speed in underwater undulatory swimming

Undulatory swimming is the predominant form of locomotion in aquatic vertebrates. A myriad of animals of different species and sizes oscillate their bodies to propel themselves in aquatic environments with swimming speed scaling as the product of the animal length by the oscillation frequency. Although frequency tuning is the primary means by which a swimmer selects its speed, there is no consensus on the mechanisms involved. In this article, we propose scaling laws for undulatory swimmers that relate oscillation frequency to length by taking into account both the biological characteristics of the muscles and the interaction of the moving swimmer with its environment. Results are supported by an extensive literature review including approximately 1200 individuals of different species, sizes and swimming environments. We highlight a crossover in size around 0.5-1 m. Below this value, the frequency can be tuned between 2-20 Hz due to biological constraints and the interplay between slow and fast muscles. Above this value, the fluid-swimmer interaction must be taken into account and the frequency is inversely proportional to the length of the animal. This approach predicts a maximum swimming speed around 5-10 m.s-1 for large swimmers, consistent with the threshold to prevent bubble cavitation.

Development of an underwater networking system using bio-inspired electrocommunication

Current underwater communication typically includes acoustic, optical, radio frequency, and magneto-inductive channels. Wireless sensor networks are usually built on these four channels. However, these underwater networks are vulnerable to complex aquatic environments. In nature, weakly electric fish are able to communicate electrically (called electrocommunication), which is 'invisible' to most other animals, to convey information such as species, courtship, and environmental conditions. Inspired by the electrocommunication of weakly electric fish, an artificial electrocommunication system that uses an electric induction (EI) channel has been developed recently. This paper further develops an underwater networking system using the EI channel, which addresses the solutions to collision avoidance and routing problems during electrocommunication networking. In particular, a CSMA/CA-based electrocommunication mechanism was used to solve the collision problem. Then, a single-hop underwater electrocommunication network (UEN) was established. Furthermore, a complex multi-hop UEN was implemented on the basis of the ad hoc on-demand distance vector routing protocol. Theoretical analysis, simulations, and experiments were conducted to demonstrate the effectiveness of the developed UEN. Extensive results show that the UEN holds the potential to serve as a complement to future underwater wireless sensor networks.

Minimal sensor arrays for localizing objects using an electric sense

Weakly electric fish encode perturbations in a self-generated electric field to sense their environment. Localizing objects using this electric sense requires that distance be decoded from a two-dimensional \emph{electric image} of the field perturbations on their skin. Many studies of object localization by weakly electric fish, and by electric sensing in a generic context, have focused on extracting location information from different features of the electric image. Some of these studies have also considered the additional information gained from sampling the electric image at different times, and from different viewpoints. Here, we take a different perspective and instead consider the information available at a single point in space (i.e. a single sensor or receptor) at a single point in time (i.e. constant field). By combining the information from multiple receptors, we show that an object's distance can be unambiguously encoded by as few as four receptors at specific locations on a sensing surface in a manner that is relatively robust to environmental noise. This provides a lower bound on the information (i.e. receptor array size) required to decode the three-dimensional location of an object using an electric sense.

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.

Underwater pre-touch based on artificial electric sense

This article exploits a bio-inspired sensor technology named artificial electric-sense to emulate underwater pre-touch. The sensor is considered as an electric finger controlled remotely by an operator to follow the boundaries of objects. Using electric measurements only, the approach feeds back pre-touch forces and torques to the operator through an haptic interface. These forces and torques are generated by a set of virtual electric charges and dipoles arranged on the probe and reacting in the electric field reflected by the objects. This model of emulated forces is passive and guarantees the stability of a position–position haptic feedback loop. The whole approach is assessed through a set of experiments carried out on a Cartesian slave robot coupled to an haptic interface. The obtained results show the feasibility of the concept and its robustness to different configurations of objects. Such an electro-haptic feedback opens new perspectives in both electric field sensing and underwater robotics.

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 Heterogeneous Robotic Swarm for Long-Term Monitoring of Marine Environments

This paper describes an underwater acoustic sensor network consisting of a heterogeneous robotic swarm used for long-term monitoring of underwater environments. The swarm consists of a large number of underwater robots acting as sensor nodes with limited movement capabilities, and a few surface robots aiding them in accomplishing underwater monitoring scenarios. Main interactions between two types of robots include underwater sensor deployment and relocation, energy and data exchange, and acoustic localisation aiding. Hardware capabilities of each vehicle are described in detail. Inter-agent communication is split into two layers: surface and underwater communication. Surface communication utilises wireless communication using WiFi routers configured for decentralised routing. Underwater communication mainly uses acoustic communication which, when used within a large swarm, poses a challenging task because of high probability of interference and data loss. The acoustic communication protocol used to prevent these issues is presented in detail. Finally, more complex functionalities of the robotic swarm are presented, including several results from real-life experiments.

Spatiotemporal model for depth perception in electric sensing

Electric sensing involves measuring the voltage changes in an actively generated electric field, enabling an environment to be characterized by its electrical properties. It has been applied in a variety of contexts, from geophysics to biomedical imaging. Some species of fish also use an active electric sense to explore their environment in the dark. One of the primary challenges in such electric sensing involves mapping an environment in three-dimensions using voltage measurements that are limited to a two-dimensional sensor array (i.e. a two-dimensional electric image). In some special cases, the distance of simple objects from the sensor array can be estimated by combining properties of the electric image. Here, we describe a novel algorithm for distance estimation based on a single property of the electric image. Our algorithm can be implemented in two simple ways, involving either different electric field strengths or different sensor thresholds, and is robust to changes in object properties and noise.

Application of reduced sensor movement sequences as a precursor for search area partitioning and a selection of discrete EEV contour-ring fragments for active electrolocation

In addition to their visual sense, weakly electric fish use active electrolocation to detect and analyse objects in their nearby environment. Their ability to generate and sense electric fields combined with scanning-like swimming movements are intended to extract further parameters like the size, shape and material properties of objects. Inspired by this biological example, this work introduces an application for active electrolocation based on reduced sensor movement sequences as presented in Wolf-Homeyer et al (2016 Bioinspir. Biomim. 11 055002). Initially, the application is conducted with a simulated receptor-system consisting of an emitter-dipole and an orthogonally arranged pair of sensor-electrodes. Close inspection of a minimal set of scanning movements allows the exclusion of sectors of the general search area early in the proposed localization algorithm (search area partitioning). Furthermore, the proposed algorithm is based on an analytical representation of the electric field and of the so-called EEV (ensemble of electrosensory viewpoints) (Solberg et al 2008 Int. J. Robot. Res. 27 529-48) rather than using computationally expensive FEM simulations, rendering it suitable for embedded computer systems. Two-dimensional discrete EEV contour-ring points (CRPs) of desired accuracy are extracted. In the core of the localization algorithm, fragments of the EEV are selected from valid sectors of the search area, which generates sets of CRPs, one for each sensor-emitter position/orientation. These sets are investigated by means of a nearness metric to find points in different sets which correspond to each other in order to estimate the object position. Two resultant scanning strategies/localization algorithms are introduced.

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.