Low-cost Autonomous Underwater Vehicles Research Articles

Sim-to-real transfer of adaptive control parameters for AUV stabilisation under current disturbance

Learning-based adaptive control methods hold the potential to empower autonomous agents in mitigating the impact of process variations with minimal human intervention. However, their application to autonomous underwater vehicles (AUVs) has been constrained by two main challenges: (1) the presence of unknown dynamics in the form of sea current disturbances, which cannot be modelled or measured due to limited sensor capability, particularly on smaller low-cost AUVs, and (2) the nonlinearity of AUV tasks, where the controller response at certain operating points must be excessively conservative to meet specifications at other points. Deep Reinforcement Learning (DRL) offers a solution to these challenges by training versatile neural network policies. Nevertheless, the application of DRL algorithms to AUVs has been predominantly limited to simulated environments due to their inherent high sample complexity and the distribution shift problem. This paper introduces a novel approach by combining the Maximum Entropy Deep Reinforcement Learning framework with a classic model-based control architecture to formulate an adaptive controller. In this framework, we propose a Sim-to-Real transfer strategy, incorporating a bio-inspired experience replay mechanism, an enhanced domain randomisation technique, and an evaluation protocol executed on a physical platform. Our experimental assessments demonstrate the effectiveness of this method in learning proficient policies from suboptimal simulated models of the AUV. When transferred to a real-world vehicle, the approach exhibits a control performance three times higher compared to its model-based nonadaptive but optimal counterpart.

Feedback error-state Kalman filter with time-delay compensation for hydroacoustic-aided inertial navigation of underwater vehicles

This article is intended as a tutorial to assist engineers who want to develop and implement low-cost underwater vehicle inertial navigation systems (INS) aided by time-delayed hydroacoustic position measurements. A discrete-time unit quaternion error-state Kalman filter (ESKF) is used for sensor fusion. The ESKF is implemented as a feedback algorithm with reset functionality. This is motivated by the need for long-endurance autonomous underwater vehicles (AUVs). Proprietary navigation systems do not allow users to add more measurement equations to the code if additional sensors are available. However, the open-source filter architecture presented in the article provides for this. The article also aims to make in-house development of strapdown INS accessible and affordable for vendors of low-cost AUV systems. Finally, a case study of an AUV with a standard sensor suite is included to demonstrate the performance of the ESKF aided by time-delayed position measurements.

Underwater ice adaptive mapping and reconstruction using autonomous underwater vehicles

The undersides of floating ice shelves and sea ice in the Antarctic and Arctic are among the least accessible environments on Earth. The interactions between ice shelves, sea ice, and the ocean are of considerable scientific interest. In order to fully understand the complex picture of sea ice, and not just its surface, it is quite necessary to map the underside to comprehend the full context of its growth and decay patterns. Autonomous Underwater Vehicles (AUVs) are rapidly becoming the desired platform of choice for mapping the underside of sea ice to provide high-resolution 3D views of sea ice topography. To increase the efficiency and accuracy of AUV sampling behaviors is significant for the under-ice observation mission given its limited endurance. In this paper, we present a low-cost underwater ice mapping framework for small-sized AUVs using adaptive sampling and map reconstruction methods. A small-sized AUV is cost-effective and convenient for operation in polar regions; however, due to its limited loading capacity and energy, it is more applicable for the vehicle to carry single-beam sonar for ice bottom mapping but not multi-beam. Thus, the essential issue in this application is how to obtain the key information of ice topography and how to reconstruct the map of ice draft (namely underwater ice thickness) with AUV sparse mapping swathes. To address this, we propose a graphics-based adaptive mapping method to densify the measuring of ice bottom surface with ‘noticeable’ variations; moreover, we also present a sparse approximation method for ice draft map reconstruction using the sparse mapping swathes from a single-beam sonar. Our efforts are to introduce an effective and efficient approach for underwater ice mapping using low-cost small-sized AUVs. Our proposed adaptive mapping and reconstruction methods are validated in the under-ice scenario created using the field data.

A Software-Defined Underwater Acoustic Modem for Everyone: Design and Evaluation

The development of small low-cost autonomous underwater and surface vehicles has increased the need for underwater wireless communication and ranging to support swarm operations for collaborative data collection efforts. Specifically, newly available low-cost underwater and surface vehicles make the realization of swarm formation cost effective. However, their mission coordination involves the use of expensive acoustic modems whose price may be higher than that of the vehicle itself. In this paper, we describe and evaluate a low-cost software-defined acoustic modem developed with only off-the-shelf components, able to perform one-way travel-time ranging. The modem is specifically designed for dense mobile networks deployed in shallow water environments, such as rivers, lagoons and lakes. The modular software design of the modem allows us to easily configure parameters such as modulation and coding schemes, scheduling algorithm, source power, carrier frequency and bandwidth. In this paper we evaluate, in a shallow environment, the modem performance in terms of packet detection ratio, packet delivery ratio, and one-way travel-time ranging.

Survey on Low-Cost Underwater Sensor Networks: From Niche Applications to Everyday Use

Traditionally, underwater acoustic modems and positioning systems were developed for military and Oil & Gas industries, that require deep water deployments and extremely reliable systems, focusing on high power expensive systems and leaving the use of low-cost devices only attractive for academic studies. Conversely, recent developments of low-cost unmanned vehicles, such as remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs), suitable for shallow water coastal missions, and the need of sensors network deployments for measuring water quality and studying the effect of climate change in coastal areas, called to the need of low-cost and low-power acoustic modems and positioning systems that are gaining more and more momentum to date. The use of these devices can enable a wide set of applications, often based on low-cost AUV swarm formations, where an acoustic link between the vehicles is required to coordinate the mission, perform the maneuvers, and maintain the formation along the time. Moreover, they can make environmental wireless sensor deployment cost effective by substituting wired systems. Underwater positioning systems, usually used in large-scale operations, can be finally applied to small-scale application thanks to the reduction in costs, at the price of a lower transmission and positioning range and precision. While in open-sea application this performance reduction is a huge limitation, in river, lagoon, port and lake deployments this is not an issue, given that the extremely shallow water and the presence of many obstacles would deteriorate the acoustic signal anyway, not allowing long range transmissions even with expensive and sophisticated acoustic devices. In this paper, we review the recent developments of low-cost and low-power acoustic communication and positioning systems, both analyzing University prototypes and new commercial devices available in the market, identifying advantages and limitations of these devices, and we describe potential new applications that can be enabled by these systems.

Wide-Area Three-Dimensional Imaging of Mesophotic Coral Reefs Using a Low-Cost AUV

Abstract Surveys and monitoring are essential to study the biology and ecology of coral reefs in order to understand the reasons behind reef demise and recovery. However, mesophotic coral ecosystems (MCEs) remain largely unknown compared to their shallow counterparts because it is difficult to observe the seafloor below 30 m depths. Here, we propose a seafloor observation method using a low-cost autonomous underwater vehicle (AUV). This method was developed to allow many people to easily perform underwater observations of MCEs, and is also applicable to general seafloor surveys, such as underwater artificial structures, hydrothermal vent fields, etc. The method possesses three important attributes to achieve effective surveys. First, it can be applied in highly rugged terrains and enables the AUV to track omnidirectional surfaces at high speed (Max. ~1 m/s). Second, it can produce a reliable three-dimensional (3D) image of the seafloor based on a depth sensor. Third, it can be used to estimate the flow velocity field. The proposed method was tested by using the AUV HATTORI-2, which is a lightweight, one-man portable AUV equipped with commercial off-the-shelf sensors. Our study area is the Sekisei Lagoon in the South Ryukyus, which represents the largest coral reef complex in Japan. The method enabled us not only to obtain a wide and high-definition 3D image of mesophotic coral reefs that captures detailed characteristics of marine habitats but also to acquire environmental data, such as flow velocity field and seawater temperature, spatially and temporally aligned with the 3D image.

Synchronous-Clock Range-Angle Relative Acoustic Navigation: A Unified Approach to Multi-AUV Localization, Command, Control, and Coordination

This paper presents a scalable acoustic navigation approach for the unified command, control, and coordination of multiple autonomous underwater vehicles (AUVs). Existing multi-AUV operations typically achieve coordination manually by programming individual vehicles on the surface via radio communications, which becomes impractical with large vehicle numbers; or they require bi-directional intervehicle acoustic communications to achieve limited coordination when submerged, with limited scalability due to the physical properties of the acoustic channel. Our approach utilizes a single, periodically broadcasting beacon acting as a navigation reference for the group of AUVs, each of which carries a chip-scale atomic clock and fixed ultrashort baseline array of acoustic receivers. One-way travel-time from synchronized clocks and time-delays between signals received by each array element allow any number of vehicles within receive distance to determine range, angle, and thus determine their relative position to the beacon. The operator can command different vehicle behaviors by selecting between broadcast signals from a predetermined set, while coordination between AUVs is achieved without intervehicle communication by defining individual vehicle behaviors within the context of the group. Vehicle behaviors are designed within a beacon-centric moving frame of reference, allowing the operator to control the absolute position of the AUV group by repositioning the navigation beacon to survey the area of interest. Multiple deployments with a fleet of three miniature, low-cost SandShark AUVs performing closed-loop acoustic navigation in real-time provide experimental results validated against a secondary long-baseline positioning system, demonstrating the capabilities and robustness of our approach with real-world data.

Development of Low Cost Autonomous Underwater Vehicle Platform

Abstract This paper presents the development of a low-cost autonomous underwater vehicle (AUV). For research, industrial and military underwater applications, AUVs are generally used, which modeling, system identification and control of these vehicles pose serious challenges due to the vehicles’ complex, inherently nonlinear, and time-varying dynamics. Here, the AUV is considered to have 6-DOF for the development of the electrical, electronics, power distribution, sensors, and actuators. A low-cost IMU is used along with other reasonably low-cost detectors, such as a magnetometer and a water pressure sensor for depth evaluation. This study addresses the configuration and selection of the onboard instruments required to collect data using a processing unit (PC104) based on-board data logger to record complete manoeuvring data obtained from various sensors and process it based on the experiment. Real-time validations using Hardware-in-Loop (HIL) simulations are carried out. HIL simulations help to simulate the behavior of the developed model for surge, pitch and yaw movement, and also it makes clear that the used identification methods are feasible for real time control. Real time experiments are carried out with the developed 6-DOF instrumented AUV platform in various conditions and environments to validate its dynamics identification with adaptive controller and the results are presented for surge, the control of pitch, and yaw. The results revealed that the adaptive controller can effectively control the developed AUV and show its robust properties in the real world.

Enhanced State Estimation Based on Particle Filter and Sensor Data With Non-Gaussian and Multimodal Noise

This paper presents a novel approach to state estimation based on particle filter dealing with measurement data effected by non-Gaussian, multimodal noise. The implementation focusses on autonomous underwater vehicles (AUVs) utilizing data of a magnetic compass and a mechanical scanning sonar for spatial navigation. Nowadays, particle filter approaches often require complicated feature extraction methods culminating in semantic interpretation of the data. This is not suitable for low-cost and low-weight AUVs, because these steps require high computational power. Therefore, efficient CPUs and higher power delivery are required. To test the novel approach, the algorithm is simulated in different scenarios with different parameters. Additionally, the filter is applied to real environment data. Finally, the performance is tested and evaluated by several methods. We demonstrate the computational efficiency and superiority of our method over other approaches through simulations.

Cruise Speed Estimation Strategy Based on Multiple Fuzzy Logic and Extended State Observer for Low-Cost AUV

This article presents an effective cruise speed estimation strategy for low-cost autonomous underwater vehicles under the impact of complex ocean currents and the absence of critical navigation sensors. The estimation strategy is based on the motor feedback information, including motor current and propeller speed. The cruise speed estimation strategy requires a rough speed estimation and minor adjustments to ensure that the estimated speed is valuable. In this article, the multiple fuzzy logic is applied to generate the mapping between the motor current deviation, propeller speed, and cruise speed deviation. Afterward, recursive least square is introduced to fine-tune the rough speed based on the reference propeller torque estimated by extended state observer. The experimental results demonstrate that the estimated speed of the proposed method can reach, on average, 96% of the Doppler velocity log measurement accuracy under the ocean currents conditions. The experimental results also illustrate that the method proposed in this article has strong robustness.

Automated fish cage net inspection using image processing techniques

Fish-cage dysfunction in aquaculture installations can trigger significant negative consequences affecting the operational costs. Low oxygen levels, due to excessive fooling's, leads to decrease growth performance, and feed efficiency. Therefore, frequent periodic inspection of fish-cage nets is required, but this task can become quite expensive with the traditional means of employing professional divers that perform visual inspections at regular time intervals. The modern trend in aquaculture is to take advantage of IT technologies with the use of a small-sized, low-cost autonomous underwater vehicle, permanently residing within a fish cage and performing regular video inspection of the infrastructure for the entire net surface. In this study, we explore specialised image processing schemes to detect net holes of multiple area size and shape. These techniques are designed with the vision to provide robust solutions that take advantage of either global or local image structures to provide the efficient inspection of multiple net holes.

Tracking Omnidirectional Surfaces Using a Low-Cost Autonomous Underwater Vehicle

Tracking and observing underwater structures at close range are important for gathering high-resolution information. This article proposes a method to track omnidirectional surfaces using an autonomous underwater vehicle (AUV). This method is suitable for surveying various kinds of underwater structures, such as rugged seafloors, ship hulls, pools, dams, and quay walls. It is based on stochastic means, and has two important features. First, it depends on only commercial off-the-shelf sensors (mechanical scanning imaging sonar, a water current sensor, and an attitude sensor). Second, it is applicable to fast moving vehicles. This method is implemented in the AUV highly agile terrain tracker for ocean research and investigation, and verification tests in the sea and in a tank are carried out to evaluate its performance. In the sea, the AUV succeeded in tracking the rugged seafloor at high speed. In the tank, the AUV succeeded in tracking vertical walls while keeping its roll angle at 90$^\circ$.

Differential Pressure Sensor Speedometer for Autonomous Underwater Vehicle Velocity Estimation

Velocity estimation is central for the reliable navigation of autonomous underwater vehicles (AUVs). Doppler velocity logs (DVLs), currently the leading technology for underwater velocity estimation, can be too big, expensive, and energy consuming to be used on low-cost and small AUVs or for long missions. In our previous work, a system based on differential pressure sensors was developed for estimating surge velocity. In this paper, we combine this system with an inertial measurement unit to compensate for orientation errors and create a differential pressure sensor speedometer (DPSS). We propose and demonstrate the DPSS prototype as an important step toward a small, inexpensive, and energy-efficient alternative or complement to a DVL in certain applications. This paper presents the first underwater field tests of a sensor using differential pressure for velocity estimation. Tests were conducted with a SPARUS II AUV (IQUA Robotics, Girona, Spain). To demonstrate the efficacy of our proposed solution, we compare the surge velocity estimation of the DPSS and the vehicle's DVL in bottom and water locks. Trials were conducted by varying the trajectory and velocity of the vehicle in three different environments. We show that the DPSS displayed a superior performance with respect to the DVL water lock for velocities above 0.6 m/s. The differences in the velocity estimations of the DVL in bottom lock for high velocities were as small as 0.013 m/s. These results encourage further development of the presented technology.

Relative Autonomy and Navigation for Command and Control of Low-Cost Autonomous Underwater Vehicles

The underwater environment severely constrains robotic navigation and communications, making the use of traditional multi-robot control and coordination schemes very difficult. These challenges are exacerbated on a new generation of low-cost autonomous underwater vehicles (AUVs) that lack a Doppler velocity log, acoustic modem, or high-end inertial sensors typically used for underwater robotic navigation and communications.This letter demonstrates multi-robot operations for low-cost AUVs via a novel and user-friendly operating paradigm that allows intuitive command and control of an AUV group. Each vehicle is equipped with a low-power and inexpensive acoustic system for navigation and receipt of operator commands. This system consists of a passive array of hydrophones and a timed acquisition and data processing stack that allows each AUV to self-localize relative to a time-synchronized acoustic beacon. Switching between different operational “modes” on the beacon causes it to broadcast different acoustic signals which, when received by the AUVs, result in the vehicles switching between different autonomous behaviors. These behaviors are defined in a beacon-centric coordinate system using pre-defined parameters unique to each vehicle; as a result, the movement of the beacon itself allows the operator to control the group-wide movement of all vehicles concurrently. This letter presents field experiments with three SandShark AUVs in which operational mode and beacon movement were controlled by an operator. However, by installing the beacon on an autonomous vehicle, this paradigm would provide a method for remote command and control of an arbitrarily large number of miniature, low-cost AUVs, without the need for sophisticated navigational sensors or acoustic modems.

A Low-cost Electromagnetic Docking Guidance System for Micro Autonomous Underwater Vehicles

As important observational platforms for the Smart Ocean concept, autonomous underwater vehicles (AUVs) that perform long-term observation in fleets are beneficial because they provide large-scale sampling data with a sufficient spatiotemporal resolution. Therefore, a large number of low-cost micro AUVs with docking capability for power recharge and data transmission are essential. This study designed a low-cost electromagnetic docking guidance (EMDG) system for micro AUVs. The EMDG system is composed of a transmitter coil located on the dock and a three-axial search coil magnetometer acting as a receiver. The search coil magnetometer was optimized for small sizes while maintaining sufficient sensitivity. The signal conditioning and processing subsystem was designed to calculate the deflection angle (β) for docking guidance. Underwater docking tests showed that the system can detect the electromagnetic signal and successfully guide AUV docking. The AUV can still perform docking in extreme positions, which cannot be realized through normal optical or acoustic guidance. This study is the first to focus on the EM guidance system for low-cost micro AUVs. The search coil sensor in the AUV is inexpensive and compact so that the system can be equipped on a wide range of AUVs.

Relative navigation for command and control of multiple low-cost autonomous underwater vehicles

A long-held goal of autonomous underwater vehicle (AUV) research has been the coordinated use of multiple vehicles for novel applications. Unfortunately, the underwater domain poses significant challenges for navigation and communication—sophisticated navigational sensors increase vehicle price, size, and power use, and acoustic communications are limited in bandwidth and channel capacity. These factors make multi-vehicle deployments rare and limited in scale, with operators commanding each AUV individually and with limited coordination. In this work, we describe an operating paradigm that enables user-friendly command and control of multiple AUVs. Each vehicle uses a custom low-power, low-cost acoustic system to navigate and receive operator commands, consisting of a passive hydrophone array and timed acquisition and processing boards which enable the vehicle to self-localize relative to a synchronized acoustic beacon. By selecting between various beacon-transmitted signals, all vehicles can be simultaneously commanded to switch between behaviors. Additionally, a consequence of beacon-relative navigation is that movement of the beacon results in the concurrent movement of all AUVs. This system is ideal for multi-vehicle operations using inexpensive, miniature AUVs, as it does not require conventional high-cost navigational sensors or acoustic modems, and its passive nature and associated operating scheme enable the deployment of an arbitrarily large number of AUVs. [Work supported by Battelle, ONR, Lincoln Laboratory, DARPA.]

The ARROWS Project: robotic technologies for underwater archaeology

The paper summarizes the main results achieved during the three-year European FP7 ARROWS project (ARchaeological RObot systems for the Worlds Seas). ARROWS concluded at the end of August 2015 and proposed to adapt and develop low-cost Autonomous Underwater Vehicle (AUV) technologies to reduce the operational cost of typical underwater archaeological campaigns. The methodology used by ARROWS researchers identified archaeologists requirements for all the phases of a campaign. These were based on guidelines issued by the project Archaeology Advisory Group (AAG), which comprised of many European archaeologists belonging to the consortium. One of the main goals of the ARROWS project was the development of a heterogeneous team of cooperating AUVs; these comprised of prototypes developed in the project and commercially available vehicles. Three different AUVs have been built and tested at sea: MARTA, characterized by flexible hardware modularity for easy adaption of payload and propulsion systems, U-CAT, a turtle inspired bio-mimetic robot devoted to shipwreck penetration and A-Size AUV, a small light weight vehicle which is easily deployable by a single person. The project also included the development of a cleaning tool for well-known artefacts and maintenance operations. Results from the official final demonstrations of the project, held in Sicily and in Estonia during Summer 2015, are presented in the paper as an experimental proof of the validity of the developed robotic tools.

Deployment of a passive acoustic collision alarm for autonomous underwater vehicles

Autonomous underwater vehicles (AUVs) operate in increasingly busy environments, and avoiding collisions with ships is an important aspect of the vehicle's decision framework. Advances in low-cost AUV technology has further raised interest in solutions that minimize the need for specialized equipment. A proposed solution is to passively detect and track boats based on their noise. We have developed and demonstrated an algorithm that uses changes in acoustic power to estimate time to collision. A cylindrical propagation model is used for shallow-water environments, to relate measured power with range from a source. The time-derivative of this result is computed to estimate the time to closest approach, for a ship with unknown but constant acoustic source level. Experiments were performed with vessels of various characteristic frequencies and source levels. Acoustic measurements were recorded through off-the-shelf hydrophones. Estimates from the acoustic method were first compared with GPS-based measurements, and later with the AUV's on-board navigation data. Test missions were deployed to alter AUV behavior in response to approaching acoustic sources. Successful estimates and AUV responses were recorded, although improved signal processing and noise filtering is recommended for future implementations. [Work supported by Lincoln Laboratory and DARPA.]

An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles.

Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance.

A low cost autonomous underwater vehicle for patrolling and monitoring

The involvement of autonomous underwater vehicles for patrolling, monitoring or maintenance activities of submersed structures in the coastal strip, harbors or in proximity of off-shore plants (e.g. in oil& gas and military fields), can represent a high benefit for the economy of the related areas. For instance, continuous or more frequent monitoring can be possible, with a reduction of the necessary costs: The use of remotely operated vehicles with the linked implication of support ships and specialized pilots, or the involvement of professional divers, could be avoided or significantly reduced. The paper describes the FeelHippo autonomous underwater vehicles, the vehicle designed and built by the MDM Lab of the University of Florence; it is a low cost autonomous underwater vehicles suitable for these purposes. In particular, an onboard acoustic localization system, based on a low cost approach, has been implemented and preliminary experimental results are here reported.