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A Hybrid Underwater Acoustic and RF Localisation System for Enclosed Environments Using Sensor Fusion: 19th Annual Conference, TAROS 2018, Bristol, UK July 25-27, 2018, Proceedings
Abstract
Underwater localisation systems are traditionally based on acoustic range estimation, which lacks the accuracy to localise small underwater vehicles in enclosed structured environments for mapping and surveying purposes. The high attenuation of electromagnetic waves underwater can be exploited to obtain a more precise distance estimation over short distances. This work proposes a cooperative localisation system that combines an acoustic absolute localisation system with peer-to-peer distance estimation based on electromagnetic radio frequency (RF) attenuation between multiple robots. The proposed system is able to improve the position estimation of a group of Autonomous Underwater Vehicles (AUVs) or Remote Operated Vehicles (ROVs) for exploring enclosed environments.
The EU-funded CoCoRo project studies heterogeneous swarms of AUVs used for the purposes of under water monitoring and search. The CoCoRo underwater swarm system will combine bio-inspired motion principles with biologically-derived collective cognition mechanisms to provide a novel robotic system that is scalable, reliable and flexible with respect its behavioural potential. We will investigate and develop swarm-level emergent self-awareness, taking biological inspiration from fish, honeybees, the immune system and neurons. Low-level, local information processing will give rise to collective-level memory and cognition. CoCoRo will develop a novel bio-inspired operating system whose default behaviour will be to provide AUV shoaling functionality and the maintenance of swarm coherence. Collective discrimination of environmental properties will be processed on an individual-or on a collective-level given the cognitive capabilities of the AUVs. We will investigate collective self-recognition through experiments inspired by ethology and psychology, allowing for the quantification of collective cognition.
In this paper we discuss challenging issues related to positioning in underwater acoustic networks focussing in the major goal of establishing a common coordinate system which should allow applications to perform collaborative sensing tasks such as identification, detection, and/or tracking of sea targets. A general description of the most important positioning methods and algorithms which have been proposed, developed and employed in the underwater environment is provided along with their major advantages and requirements. Also the applicability to the underwater acoustic scenario is discussed. Finally we argue the need of a new ad-hoc positioning scheme adapted to the underwater acoustic environment and an outlook of our future work is given.
The practical deployment of wireless positioning systems requires minimizing the calibration procedures while improving the location estimation accuracy. Received Signal Strength localization techniques using propagation channel models are the simplest alternative, but they are usually designed under the assumption that the radio propagation model is to be perfectly characterized a priori. In practice, this assumption does not hold and the localization results are affected by the inaccuracies of the theoretical, roughly calibrated or just imperfect channel models used to compute location. In this paper, we propose the use of weighted multilateration techniques to gain robustness with respect to these inaccuracies, reducing the dependency of having an optimal channel model. In particular, we propose two weighted least squares techniques based on the standard hyperbolic and circular positioning algorithms that specifically consider the accuracies of the different measurements to obtain a better estimation of the position. These techniques are compared to the standard hyperbolic and circular positioning techniques through both numerical simulations and an exhaustive set of real experiments on different types of wireless networks (a wireless sensor network, a WiFi network and a Bluetooth network). The algorithms not only produce better localization results with a very limited overhead in terms of computational cost but also achieve a greater robustness to inaccuracies in channel modeling.
This paper reports the development of a new hydrodynamics test facility for UUV dynamics, navigation, and control research. Located at the Johns Hopkins University, the facility's 174,000 liter water tank, navigation instrumentation, and testbed ROV provides the ability for development of advanced underwater vehicle systems. Experimental data demonstrating the performance of the facility's sensor suite is presented. This paper briefly discusses the facility's recent role in the development of control and navigation systems for operational oceanographic underwater vehicles.
The AVEXIS (aqua vehicle explorer for in-situ sensing) underwater vehicles have been developed to allow characterization and monitoring of hazardous underwater environments with limited access points. A number of forms of the vehicle are being developed to assist in the decommissioning of the Sellafield nuclear facilities in Cumbria, U.K. The vehicles have been designed to be low-cost and have been constructed using novel manufacturing methods, such as 3D printing, which allows them to be built quickly and adds a high level of flexibility to the design. An acoustic communications and positioning system has also been developed which can be integrated into the vehicle or used as a stand-alone system which can be retrofitted onto existing vehicles.
This paper addresses the development of an underwater visual navigation system for a Remotely Operated Vehicle (ROV) based on Real-Time Simultaneous Localization and Mapping method using natural landmarks. Our proposed approach was tested in an indoor tank, where field experiments were performed to obtain 3D vehicle (VIDEORAY Pro3 ROV) trajectory, and results validated using an external stereo vision 'ground-truth' system.
This paper describes a communication and localization system for micro-autonomous underwater vehicles (µAUVs) undertaking monitoring and mapping tasks in nuclear storage ponds. A distinctive feature of this underwater environment is the severe multipath propagation and long reverberation times. The paper describes how a common code division multiplexed signal format is used to mitigate the acoustic channel impairments and to achieve both communication and localisation. The system consists of an onshore base-station, equipped with a four-element distributed transceiver antenna, and underwater acoustic modems installed in the µAUVs. The system simultaneously provides localisation of a swarm of µAUVs, with addressed transmission of navigation commands from the base- station to µAUVs, and telemetry data transmission to the base-station from the µAUV.
In this paper, we discuss a novel underwater short-range sensor using electromagnetic (EM) wave attenuation. We use the revised Friis–Shelkunoff formula to calculate the EM wave attenuation underwater as a function of distance. This requires knowledge of the antenna gain underwater, which is very different from the gain in air, and also the attenuation constant which depends on the water conductivity. We calibrated the gain and attenuation in a ranging experiment and also in a 2-D localization experiment. Both methods agreed, confirming that in situ calibration of a 2-D localization experiment is feasible. The localization results show good accuracy, validating the sensor model and showing that multipath effects can be made negligible in such an experiment.
In this paper, we discuss a feasibility of novel underwater localization system using EM wave. In structured environment, we confirmed a linear RSSI attenuation by distance.
Underwater Wireless Sensor Networks (UWSNs) are expected to support a variety of civilian and military applications. Sensed data can only be interpreted meaningfully when referenced to the location of the sensor, making localization an important problem. While global positioning system (GPS) receivers are commonly used in terrestrial WSNs to achieve this, this is infeasible in UWSNs as GPS signals do not propagate through water. Acoustic communications is the most promising mode of communication underwater. However, underwater acoustic channels are characterized by harsh physical layer conditions with low bandwidth, high propagation delay and high bit error rate. Moreover, the variable speed of sound and the non-negligible node mobility due to water currents pose a unique set of challenges for localization in UWSNs. In this paper, we provide a survey of techniques and challenges in localization specifically for UWSNs. We categorize them into (i) range-based vs. range-free techniques; (ii) techniques that rely on static reference nodes vs. those who also rely on mobile reference nodes, and (iii) single-stage vs. multi-stage schemes. We compare the schemes in terms of localization speed, accuracy, coverage and communication costs. Finally, we provide an outlook on the challenges that should be, but have yet been, addressed.
Given a set of pairwise distance estimates between nodes, it is often of interest to generate a map of node locations. This is an old nonlinear estimation problem that has recently drawn interest in the signal processing community, due to the emergence of wireless sensor networks. Sensor maps are useful for estimating the spatial distribution of measured phenomena, and for routing purposes. We propose a two-stage algorithm that combines algebraic initialization and gradient descent. In particular, we borrow an algebraic solution known as Fastmap from the database literature, adapt it to the sensor network context, and motivate the placement of anchor/pivot nodes on the edges of the network. When all nodes can estimate their distance from the anchors, the overall algorithm offers very competitive performance at low complexity (quadratic in the number of nodes).
Combined multiuser acoustic communication and localisation system for
- A Dikarev
- A Griffiths
- S Watson
- B Lennox
- P Green