Design and development of autonomous robotic fish for object detection and tracking

In this article, an autonomous robotic fish is designed for underwater operations like object detection and tracking along with collision avoidance. The computer-aided design model for prototype robotic fish is designed using the Solid Works® software to export an stereolithography (STL) file to MakerBot, a 3D printer, to manufacture the parts of robotic fish using polylactic acid thermoplastic polymer. The precise maneuverability of the robotic fish is achieved by the propulsion of a caudal fin. The oscillation of the caudal fin is controlled by a servomotor. A combination of visual and ultrasonic sensors is used to track the position and distance of the desired object with respect to the fish and also to avoid the obstacles. The robotic fish has the ability to detect an object up to a distance of 90 cm at normal exposure conditions. A computational fluid dynamics analysis is conducted to analyze the fluid hydrodynamics (flow rate of water and pressure) around the hull of a robotic fish and the drag force acting on it. A series of experimental results have shown the effectiveness of the designed underwater robotic fish. </jats:p

A multirobot platform based on autonomous surface and underwater vehicles with bio-inspired neurocontrollers for long-term oil spills monitoring

This paper describes the BUSCAMOS-Oil monitoring system, which is a robotic platform consisting of an autonomous surface vessel combined with an underwater vehicle. The system has been designed for the long-term monitoring of oil spills, including the search for the spill, and transmitting information on its location, extent, direction and speed. Both vehicles are controlled by two different types of bio-inspired neural networks: a Self-Organization Direction Mapping Network for trajectory generation and a Neural Network for Avoidance Behaviour for avoiding obstacles. The systems’ resilient capabilities are provided by bio-inspired algorithms implemented in a modular software architecture and controlled by redundant devices to give the necessary robustness to operate in the difficult conditions typically found in long-term oil-spill operations. The efficacy of the vehicles’ adaptive navigation system and long-term mission capabilities are shown in the experimental results.This work was partially supported by the BUSCAMOS Project (ref. 1003211003700) under the program DN8644 COINCIDENTE of the Spanish Defense Ministry, the “Research Programme for Groups of Scientific Excellence at Region of Murcia” of the Seneca Foundation (Agency for Science and Technology of the Region of Murcia-19895/GERM/15)”, and the Spanish Government’s cDrone (ref. TIN2013-45920-R) and ViSelTR (ref. TIN2012-39279) projects

Particle Swarm Optimization Based Source Seeking

Signal source seeking using autonomous vehicles is a complex problem. The complexity increases manifold when signal intensities captured by physical sensors onboard are noisy and unreliable. Added to the fact that signal strength decays with distance, noisy environments make it extremely difficult to describe and model a decay function. This paper addresses our work with seeking maximum signal strength in a continuous electromagnetic signal source with mobile robots, using Particle Swarm Optimization (PSO). A one to one correspondence with swarm members in a PSO and physical Mobile robots is established and the positions of the robots are iteratively updated as the PSO algorithm proceeds forward. Since physical robots are responsive to swarm position updates, modifications were required to implement the interaction between real robots and the PSO algorithm. The development of modifications necessary to implement PSO on mobile robots, and strategies to adapt to real life environments such as obstacles and collision objects are presented in this paper. Our findings are also validated using experimental testbeds.Comment: 13 pages, 12 figure

Development of a formation control algorithm to coordinate multiple biomimetic AUVs in the presence of realistic environmental constraints

Biomimetic Autonomous Underwater Vehicles (BAUVs) are a class of Uncrewed Underwater Vehicle (UUV) that mimic the propulsive and steering mechanisms of real fish. However, as with all UUVs, the range and endurance of these vehicles remains limited by the finite energy source housed on board the vehicle. Unsurprisingly, a consequence of this finite energy source is that BAUVs/UUVs are incapable of completing the large-scale oceanographic sampling missions required to drastically improve our understanding of the Earth’s oceans and its processes. To overcome this limitation, this thesis aims to investigate the feasibility of deploying a self-coordinating group of BAUVs capable of completing the aforementioned oceanic surveying missions despite the constraints of the local operating environment. To achieve this, the work presented in this thesis can be separated into four distinct parts. The first of which is the development of a suitable mathematical model that accurately models the dynamics of the RoboSalmon BAUV designed and built at the University of Glasgow. As well as ensuring the models validity, its ability to efficiently simulate multiple vehicles simultaneously is also demonstrated. The design and implementation of the formation control algorithm used to coordinate the vehicles is then presented. This process describes the alterations made to a biologically-inspired algorithm to ensure the required parallel line formation required for efficient oceanic sampling can be generated. Thereafter, the implementation of a realistic representation of the underwater communication channel and its debilitating effect on the algorithms ability to coordinate the vehicles as required is presented. The thesis then describes the incorporation of two methodologies designed specifically to overcome the limitations associated with the underwater communication channel. The first of which involves the implementation of tracking/predictive functionality while the second is a consensus based algorithm that aims to reduce the algorithms reliance on the communication channel. The robustness of these two methodologies to overcoming not only the problematic communication channel but also the inclusion of additional external disturbances is then presented. The results demonstrate that while the tracking/predictive functionality can overcome the problems associated with the communication channel, its efficiency significantly reduces when the external disturbances are taken into consideration. The consensus based methodology meanwhile generates the required formation regardless of the constraints imposed by both the communication channel and the additional external disturbances and therefore provides the more robust solution

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Insect inspired visual motion sensing and flying robots

International audienceFlying insects excellently master visual motion sensing techniques. They use dedicated motion processing circuits at a low energy and computational costs. Thanks to observations obtained on insect visual guidance, we developed visual motion sensors and bio-inspired autopilots dedicated to flying robots. Optic flow-based visuomotor control systems have been implemented on an increasingly large number of sighted autonomous robots. In this chapter, we present how we designed and constructed local motion sensors and how we implemented bio-inspired visual guidance scheme on-board several micro-aerial vehicles. An hyperacurate sensor in which retinal micro-scanning movements are performed via a small piezo-bender actuator was mounted onto a miniature aerial robot. The OSCAR II robot is able to track a moving target accurately by exploiting the microscan-ning movement imposed to its eye's retina. We also present two interdependent control schemes driving the eye in robot angular position and the robot's body angular position with respect to a visual target but without any knowledge of the robot's orientation in the global frame. This "steering-by-gazing" control strategy, which is implemented on this lightweight (100 g) miniature sighted aerial robot, demonstrates the effectiveness of this biomimetic visual/inertial heading control strategy

Autonomous Grasping Using Novel Distance Estimator

This paper introduces a novel distance estimator using monocular vision for autonomous underwater grasping. The presented method is also applicable to topside grasping operations. The estimator is developed for robot manipulators with a monocular camera placed near the gripper. The fact that the camera is attached near the gripper makes it possible to design a method for capturing images from different positions, as the relative position change can be measured. The presented system can estimate relative distance to an object of unknown size with good precision. The manipulator applied in the presented work is the SeaArm-2, a fully electric underwater small modular manipulator. The manipulator is unique in its integrated monocular camera in the end-effector module, and its design facilitates the use of different end-effector tools. The camera is used for supervision, object detection, and tracking. The distance estimator was validated in a laboratory setting through autonomous grasping experiments. The manipulator was able to search for and find, estimate the relative distance of, grasp, and retrieve the relevant object in 12 out of 12 trials.publishedVersio

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

Tracking the Fine Scale Movements of Fish using Autonomous Maritime Robotics: A Systematic State of the Art Review

This paper provides a systematic state of the art review on tracking the fine scale movements of fish with the use of autonomous maritime robotics. Knowledge of migration patterns and the localization of specific species of fish at a given time is vital to many aspects of conservation. This paper reviews these technologies and provides insight into what systems are being used and why. The review results show that a larger amount of complex systems that use a deep learning techniques are used over more simplistic approaches to the design. Most results found in the study involve Autonomous Underwater Vehicles, which generally require the most complex array of sensors. The results also provide insight into future research such as methods involving swarm intelligence, which has seen an increase in use in recent years. This synthesis of current and future research will be helpful to research teams working to create an autonomous vehicle with intentions to track, navigate or survey