Oceanic Challenges to Technological Solutions : A Review of Autonomous Underwater Vehicle Path Technologies in Biomimicry, Control, Navigation, and Sensing

Autonomous Underwater Vehicles (AUVs) epitomize a revolutionary stride in underwater exploration, seamlessly assuming tasks once exclusive to manned vehicles. Their collaborative prowess within joint missions has inaugurated a new epoch of intricate applications in underwater domains. This study’s primary aim is to scrutinize recent technological advancements in AUVs and their role in navigating the complexities of underwater environments. Through a meticulous review of literature and empirical studies, this review synthesizes recent technological strides, spotlighting developments in biomimicry models, cutting-edge control systems, adaptive navigation algorithms, and pivotal sensor arrays crucial for exploring and mapping the ocean floor. The article meticulously delineates the profound impact of AUVs on underwater robotics, offering a comprehensive panorama of advancements and illustrating their far-reaching implications for underwater exploration and mapping. This review furnishes a holistic comprehension of the current landscape of AUV technology. This condensed overview furnishes a swift comparative analysis, aiding in discerning the focal points of each study while spotlighting gaps and intersections within the existing body of knowledge. It efficiently steers researchers toward complementary sources, enabling a focused examination and judicious allocation of time to the most pertinent studies. Furthermore, it functions as a blueprint for comprehensive studies within the AUV domain, pinpointing areas where amalgamating multiple sources would yield a more comprehensive understanding. By elucidating the purpose, employing a robust methodology, and anticipating comprehensive results, this study endeavors to serve as a cornerstone resource that not only encapsulates recent technological strides but also provides actionable insights and directions for advancing the field of underwater robotics.© 2024 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed

A Bioinspired Control Strategy Ensures Maneuverability and Adaptability for Dynamic Environments in an Underactuated Robotic Fish

Bioinspired underwater robots can move efficiently, with agility, even in complex aquatic areas, reducing marine ecosystem disturbance during exploration and inspection. These robots can improve animal farming conditions and preserve wildlife. This study proposes a muscle-like control for an underactuated robot in carangiform swimming mode. The artifact exploits a single DC motor with a non-blocking transmission system to convert the motor’s oscillatory motion into the fishtail’s oscillation. The transmission system combines a magnetic coupling and a wire-driven mechanism. The control strategy was inspired by central pattern generators (CPGs) to control the torque exerted on the fishtail. It integrates proprioceptive sensory feedback to investigate the adaptability to different contexts. A parametrized control law relates the reference target to the fishtail’s angular position. Several tests were carried out to validate the control strategy. The proprioceptive feedback revealed that the controller can adapt to different environments and tail structure changes. The control lawparameters variation accesses the robotic fish’s multi-modal swimming. Our solution can vary the swimming speed of 0.08 body lengths per second (BL/s), and change the steering direction and performance by an angular speed and turning curvature radius of 0.08 rad/s and 0.25 m, respectively. Performance can be improved with design changes, while still maintaining the developed control strategy. This approach ensures the robot’s maneuverability despite its underactuated structure. Energy consumption was evaluated under the robotic platform’s control and design. Our bioinspired control system offers an effective, reliable, and sustainable solution for exploring and monitoring aquatic environments, while minimizing human risks and preserving the ecosystem. Additionally, it creates new and innovative opportunities for interacting with marine species. Our findings demonstrate the potential of bioinspired technologies to advance the field of marine science and conservation

Energy Based Control System Designs for Underactuated Robot Fish Propulsion

In nature through millions of years of evolution fish and cetaceans have developed fast efficient and highly manoeuvrable methods of marine propulsion. A recent explosion in demand for sub sea robotics, for conducting tasks such as sub sea exploration and survey has left developers desiring to capture some of the novel mechanisms evolved by fish and cetaceans to increase the efficiency of speed and manoeuvrability of sub sea robots. Research has revealed that interactions with vortices and other unsteady fluid effects play a significant role in the efficiency of fish and cetaceans. However attempts to duplicate this with robotic fish have been limited by the difficulty of predicting or sensing such uncertain fluid effects. This study aims to develop a gait generation method for a robotic fish with a degree of passivity which could allow the body to dynamically interact with and potentially synchronise with vortices within the flow without the need to actually sense them. In this study this is achieved through the development of a novel energy based gait generation tactic, where the gait of the robotic fish is determined through regulation of the state energy rather than absolute state position. Rather than treating fluid interactions as undesirable disturbances and `fighting' them to maintain a rigid geometric defined gait, energy based control allows the disturbances to the system generated by vortices in the surrounding flow to contribute to the energy of the system and hence the dynamic motion. Three different energy controllers are presented within this thesis, a deadbeat energy controller equivalent to an analytically optimised model predictive controller, a $H_\infty$ disturbance rejecting controller with a novel gradient decent optimisation and finally a error feedback controller with a novel alternative error metric. The controllers were tested on a robotic fish simulation platform developed within this project. The simulation platform consisted of the solution of a series of ordinary differential equations for solid body dynamics coupled with a finite element incompressible fluid dynamic simulation of the surrounding flow. results demonstrated the effectiveness of the energy based control approach and illustrate the importance of choice of controller in performance

Super Ball Bot - Structures for Planetary Landing and Exploration, NIAC Phase 2 Final Report

Small, light-weight and low-cost missions will become increasingly important to NASA's exploration goals. Ideally teams of small, collapsible, light weight robots, will be conveniently packed during launch and would reliably separate and unpack at their destination. Such robots will allow rapid, reliable in-situ exploration of hazardous destination such as Titan, where imprecise terrain knowledge and unstable precipitation cycles make single-robot exploration problematic. Unfortunately landing lightweight conventional robots is difficult with current technology. Current robot designs are delicate, requiring a complex combination of devices such as parachutes, retrorockets and impact balloons to minimize impact forces and to place a robot in a proper orientation. Instead we are developing a radically different robot based on a "tensegrity" structure and built purely with tensile and compression elements. Such robots can be both a landing and a mobility platform allowing for dramatically simpler mission profile and reduced costs. These multi-purpose robots can be light-weight, compactly stored and deployed, absorb strong impacts, are redundant against single-point failures, can recover from different landing orientations and can provide surface mobility. These properties allow for unique mission profiles that can be carried out with low cost and high reliability and which minimizes the inefficient dependance on "use once and discard" mass associated with traditional landing systems. We believe tensegrity robot technology can play a critical role in future planetary exploration

Super Ball Bot - Structures for Planetary Landing and Exploration

Small, light-weight and low-cost missions will become increasingly important to NASA's exploration goals for our solar system. Ideally teams of dozens or even hundreds of small, collapsable robots, weighing only a few kilograms a piece, will be conveniently packed during launch and would reliably separate and unpack at their destination. Such teams will allow rapid, reliable in-situ exploration of hazardous destination such as Titan, where imprecise terrain knowledge and unstable precipitation cycles make single-robot exploration problematic. Unfortunately landing many lightweight conventional robots is difficult with conventional technology. Current robot designs are delicate, requiring combinations of devices such as parachutes, retrorockets and impact balloons to minimize impact forces and to place a robot in a proper orientation. Instead we propose to develop a radically different robot based on a "tensegrity" built purely upon tensile and compression elements. These robots can be light-weight, absorb strong impacts, are redundant against single-point failures, can recover from different landing orientations and are easy to collapse and uncollapse. We believe tensegrity robot technology can play a critical role in future planetary exploration

Intersection between natural and artificial swimmers: a scaling approach to underwater vehicle design.

Approximately 72% of the Earth’s surface is covered by water, yet only 20% has been mapped [1]. Autonomous Underwater Vehicles (AUVs) are one of the main tools for ocean exploration. The demand for AUVs is expected to increase rapidly in the coming years [2], so there is a need for faster and more energy efficient AUVs. A drawback to using this type of vehicle is the finite amount of energy that is stored onboard in the form of batteries. Science and roboticists have been studying nature for ways to move more efficiently. Phillips et al. [3] presents data that contradicts the idea that fish are better swimmers than conventional AUVs when comparing the energetic cost of swimming in the form of the Cost of Transport (COT). The data presented by Phillips et al. only applies to AUVs at higher length and naval displacement (mass) scales, so the question arises of whether an AUV built at different displacements and length scales is more efficient than biological animals and if current bio-inspired platforms are better than conventional AUVs. Besides power requirements, it is also useful to compare the kinematic parameters of natural and artificial swimmers. In this case, kinematic parameters indicate how fast the swimmer travels through the water. Also, they describe how fast the propulsion mechanism must act to reach a certain swimming speed. This research adopts the approach of Gazzola et al. [4] where the Reynolds number is associated with a dimensionless number, Swim number (Sw) in this case, that has all the kinematic information. A newly developed number that extends the swim number to conventional AUVs is the Propulsion number (Jw), which demonstrates excellent agreement with the kinematics of conventional AUVs. Despite being functionally similar, Sw and Jw do not have a one-to-one relationship. Sw, Jw, COT represent key performance metrics for an AUV, herein called performance criteria, which can be used to compare existing platforms with each other and estimate the performance of non-existent designs. The scaling laws are derived by evaluating the performance of 229 biological animals, 163 bioinspire platforms, and 109 conventional AUVs. AUVs and bio-inspired platforms have scarce data compared with biological swimmers. Only 5% of conventional and 38% of bio-inspired AUVs have kinematic data while 30% of conventional and 18% of bio-inspired AUVs have energetic data. The low amount of performance criteria data is due to the nature of most conventional AUVs as commercial products. Only recently has the COT metric been included in the performance criteria for bio-inspired AUVs. For this reason, the research here formulates everything in terms of allometric scaling laws. This type of formulation is used extensively when referring to biological systems and is defined by an exponential relationship f (x) = axb, where x is a physical parameter of the fish or vehicle, like length or displacement. Scaling laws have the added benefit of allowing comparisons with limited data, as is the case for AUVs. The length and displacement scale (physical scale) must be established before estimating the performance criteria. Scale is primarily determined by the payload needed for a particular application. For instance, surveying the water column in deep water will require different scientific tools than taking images of an oyster bed in an estuary. There is no way to identify the size of an AUV until it is designed for that application, since these scientific instruments each have their own volume, length, and weight. A methodology for estimating physical parameters using computer vision is presented to help determine the scale for the vehicle. It allows accurate scaling of physical parameters of biological and bio-inspired swimmers with only a side and top view of the platform. A physical scale can also be determined based on the vehicle’s overall volume, which is useful when determining how much payload is needed for a particular application. Further, this can be used in conjunction with 3D modeling software to scale nonexistent platforms. Following the establishment of a physical scale, which locomotion mode would be most appropriate? Unlike conventional AUVs that use propeller or glider locomotion, bio-inspired platforms use a variety of modes. Kinematics and energy expenditures are different for each of these modes. For bio-inspired vehicles, the focus will be on the body-caudal fin (BCF) locomotion, of which four types exist: anguilliform, carangiform, thunniform, and ostraciiform. There is ample research on anguilliform and carangiform locomotion modes, but little research on thunniform and ostraciiform modes. In order to determine which locomotion mode scales best for a bio-inspired AUV, this research examines the power output and kinematic parameters for all four BCF modes. In order to achieve this, computational fluid dynamics simulations are performed on a 2D swimmer for all four modes. Overset meshes are used in lieu of body-fitted meshes to increase stability and decrease computational time. These simulations were used to scale output power over several decades of Reynolds numbers for each locomotion mode. Carangiform locomotion was found to be the most energy efficient, followed by anguilliform, thunniform, and ostraciiform. In order to utilize the above scaling laws in designing a novel platform, or comparing an existing one, there must be a unifying framework. The framework for choosing a suitable platform is presented with a case study of two bio-inspired vehicles and a conventional one. The framework begins by determining how the platform can be physically scaled depending on the payload. Based on the physical scale and derived scaling laws, it then determines performance criteria. It also describes a method for relative cost scaling for each vehicle, which is not covered in the literature. The cost scaling is based on the assumption that all payloads and materials are the same. The case study shows that a conventional AUV performs better on all performance criteria and would cost less to build

Projeto e desenvolvimento do hardware e software

A presente dissertação de mestrado enquadra-se na continuação do projeto europeu Swarm of Biomimetic Underwater Vehicles. Na anterior etapa do projeto, ao nível nacional, foi construído e desenvolvido um veículo biomimético “mãe” apelidado Petinga. A segunda etapa do projeto, em fase de submissão, pretende desenvolver um swarm que contenha outros veículos, com menores capacidades operacionais e de mais baixo custo e que permitam a execução de missões de forma cooperativa. Um desses veículos será o protótipo descrito ao longo desta dissertação. Desta forma será possível utilizar um cardume de veículos biomiméticos em missões operacionais da Marinha Portuguesa, tais como Intelligence, Surveillance and Reconnaissance, Mine Counter Measures, Anti-Submarine Warfare, investigações hidrógrafas e oceanógrafas, entre outras. Nesse contexto, pretende-se construir mais veículos biomiméticos, de baixo custo, que permitam a execução de missões de forma cooperativa. Neste trabalho pretende-se construir o primeiro protótipo para um desses veículos, nas seguintes áreas: escolha de sensores, sistemas de comunicações e sistema de processamento; concepção da arquitectura de software que equipará o veículo bem como definição do middleware a utilizar; elaboração de drivers para os sensores e sistemas de comunicações que equipam o veículo; e integração e testes. O primeiro protótipo é um veículo biomimético de subsuperfície (em inglês Biomimetic Underwater Vehicle) chamado Tobias. Foi construído para ser utilizado na costa portuguesa a uma profundidade máxima de 10 metros, com uma autonomia de 2 horas e com comunicação acústica, WiFi e Global System for Mobile Communications. Com perfil biomimético, possui uma cauda, constituída por dois servos e duas barbatanas dorsais que são atuadas por um servo cada uma. Para controlo da flutuabilidade será utilizado um sistema de bexiga artificial. Ao nível dos sensores deverá ser equipado com um sonar frontal para evitar obstáculos, uma câmara, um sensor inercial, um sensor de pressão, um recetor Global Navigation Satellite System. Como unidade de comando e controlo utilizar-se-à a placa Jetson Nano que correrá o software. A framework adotada para desenvolvimento do software do veículo será o Robot Operating System.This Master’s dissertation is part of the continuation of the European project Swarm of Biomimetic Underwater Vehicles. In the previous stage of the project, on the Portuguese side, was built and developed a biomimetic vehicle “mother” nicknamed Petinga. The second stage of the project, in submission phase, intends to develop a swarm that contains other vehicles, with lower operational capacities and lower cost, that allow the execution of missions in a cooperative way. One of these vehicles will be the prototype described throughout this dissertation. This way it will be possible to use a biomimetic vehicles in operational missions of the Portuguese Navy, such as Intelligence, Surveillance and Reconnaissance, Mine Counter Measures, Anti- Submarine Warfare, hydrographic and oceanographic research, among others. In this context, it is intended to build more biomimetic vehicles, at low cost, that allow the execution of missions in a cooperative way. This work will deal with the construction of the first prototype for one of those vehicles, in the following areas: choice of sensors, communication systems and processing system; design of the software architecture that will equip the vehicle as well as definition of the middleware to be used; elaboration of drivers for the sensors and communication systems that equip the vehicle; integration and tests. The first prototype is a Biomimetic Underwater Vehicle (BUV) called Tobias. It was built to be used on the Portuguese coast at a maximum depth of 10m, with an autonomy of 2h and with acoustic communication, Wireless Fidelity and Global System for Mobile Communications. With a biomimetic profile, it has a tail, consisting of two servos, and two dorsal fins that are actuated by one servos each. For buoyancy control an artificial bladder system will be used. In sensory terms it will have to be equipped with a front sonar to avoid obstacles, a camera, an inertial sensor, a pressure sensor, an Global Navigation Satellite System receiver. As a command and control unit, the software will run the Jetson Nano board. The framework adopted to develop the vehicle software will be the Robot Operating System

Physics-based Machine Learning Methods for Control and Sensing in Fish-like Robots

Underwater robots are important for the construction and maintenance of underwater infrastructure, underwater resource extraction, and defense. However, they currently fall far behind biological swimmers such as fish in agility, efficiency, and sensing capabilities. As a result, mimicking the capabilities of biological swimmers has become an area of significant research interest. In this work, we focus specifically on improving the control and sensing capabilities of fish-like robots. Our control work focuses on using the Chaplygin sleigh, a two-dimensional nonholonomic system which has been used to model fish-like swimming, as part of a curriculum to train a reinforcement learning agent to control a fish-like robot to track a prescribed path. The agent is first trained on the Chaplygin sleigh model, which is not an accurate model of the swimming robot but crucially has similar physics; having learned these physics, the agent is then trained on a simulated swimming robot, resulting in faster convergence compared to only training on the simulated swimming robot. Our sensing work separately considers using kinematic data (proprioceptive sensing) and using surface pressure sensors. The effect of a swimming body\u27s internal dynamics on proprioceptive sensing is investigated by collecting time series of kinematic data of both a flexible and rigid body in a water tunnel behind a moving obstacle performing different motions, and using machine learning to classify the motion of the upstream obstacle. This revealed that the flexible body could more effectively classify the motion of the obstacle, even if only one if its internal states is used. We also consider the problem of using time series data from a `lateral line\u27 of pressure sensors on a fish-like body to estimate the position of an upstream obstacle. Feature extraction from the pressure data is attempted with a state-of-the-art convolutional neural network (CNN), and this is compared with using the dominant modes of a Koopman operator constructed on the data as features. It is found that both sets of features achieve similar estimation performance using a dense neural network to perform the estimation. This highlights the potential of the Koopman modes as an interpretable alternative to CNNs for high-dimensional time series. This problem is also extended to inferring the time evolution of the flow field surrounding the body using the same surface measurements, which is performed by first estimating the dominant Koopman modes of the surrounding flow, and using those modes to perform a flow reconstruction. This strategy of mapping from surface to field modes is more interpretable than directly constructing a mapping of unsteady fluid states, and is found to be effective at reconstructing the flow. The sensing frameworks developed as a result of this work allow better awareness of obstacles and flow patterns, knowledge which can inform the generation of paths through the fluid that the developed controller can track, contributing to the autonomy of swimming robots in challenging environments

A complex systems approach to education in Switzerland

The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance