2,115 research outputs found

    An Autonomous Surface Vehicle for Long Term Operations

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    Environmental monitoring of marine environments presents several challenges: the harshness of the environment, the often remote location, and most importantly, the vast area it covers. Manual operations are time consuming, often dangerous, and labor intensive. Operations from oceanographic vessels are costly and limited to open seas and generally deeper bodies of water. In addition, with lake, river, and ocean shoreline being a finite resource, waterfront property presents an ever increasing valued commodity, requiring exploration and continued monitoring of remote waterways. In order to efficiently explore and monitor currently known marine environments as well as reach and explore remote areas of interest, we present a design of an autonomous surface vehicle (ASV) with the power to cover large areas, the payload capacity to carry sufficient power and sensor equipment, and enough fuel to remain on task for extended periods. An analysis of the design and a discussion on lessons learned during deployments is presented in this paper.Comment: In proceedings of MTS/IEEE OCEANS, 2018, Charlesto

    Experiment, simulation and analysis on coupling hydrodynamic forces under key parameters for a spherical underwater exploration robot

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    As a novel underwater exploration robot, BYSQ-2 spherical robot uses the heavy pendulum to change the attitudes with the characteristics of small steering resistance and high compressive strength. However, the greater water resistance in the process of moving forward obstructs the rapid movement, because the robot has a spherical shell and only one propeller. The maximum speed was obtained only 0.6 m/s according to experimental tests and theoretical calculations. In order to improve the movement speed, the robot’s virtual assembly model was built to study the coupling hydrodynamic forces between the spherical shell and the propeller by CFD method. The coupling hydrodynamic forces were analyzed and summarized under different key structural parameters that include the pipe diameter and the shell diameter. Furthermore, in the conditions of different rotational speed, propeller thrust and water resistance of robot were simulated and calculated. According to the simulation results of the model with the appropriate structural parameters, it was demonstrated that the speed of the robot was improved obviously in the process of moving forward

    Fluctuation characteristics and rolling control for an underactuated spherical underwater exploration robot

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    Compared with other underwater exploration robots, Spherical underwater robot has an outstanding advantage for the underwater exploration, whose spherical shell has the excellent resiliency to protect the internal electronic components. In addition, this steering resistance is very small to move flexibly. In this paper, a type of spherical underwater robot with the pendulums and a propeller was studied on moving at the water bottom in a rolling manner. The structure and force were analyzed to understand that the hydrodynamic force’s affection on the robot’s rolling at the water bottom. A mathematical model was established with the mass parameters and speeding parameters. The virtual simulation environment was established in Adams software. Furthermore, the coupling fluctuation characteristics of the speed, swing angle and the torque were studied by the simulation and the experiment in a pool. The study proved that this robot not only can use the propeller to move in water, but also can roll at the water bottom by driving the spherical shell. Especially, the result also can be obtained that the robot can roll at water bottom stably by increasing the pendulum mass and lowering the motor speed

    Copebot: Underwater soft robot with copepod-like locomotion

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    It has been a great challenge to develop robots that are able to perform complex movement patterns with high speed and, simultaneously, high accuracy. Copepods are animals found in freshwater and saltwater habitats that can have extremely fast escape responses when a predator is sensed by performing explosive curved jumps. Here, we present a design and build prototypes of a combustion-driven underwater soft robot, the "copebot", that, like copepods, is able to accurately reach nearby predefined locations in space within a single curved jump. Because of an improved thrust force transmission unit, causing a large initial acceleration peak (850 Bodylength*s-2), the copebot is 8 times faster than previous combustion-driven underwater soft robots, whilst able to perform a complete 360{\deg} rotation during the jump. Thrusts generated by the copebot are tested to quantitatively determine the actuation performance, and parametric studies are conducted to investigate the sensitivities of the input parameters to the kinematic performance of the copebot. We demonstrate the utility of our design by building a prototype that rapidly jumps out of the water, accurately lands on its feet on a small platform, wirelessly transmits data, and jumps back into the water. Our copebot design opens the way toward high-performance biomimetic robots for multifunctional applications.Comment: 13 pages, 8 figures, research article. Soft Robotics, 202

    Autonomous homing and docking tasks for an underwater vehicle

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    This paper briefly introduces a strategy for autonomous homing and docking tasks using an autonomous underwater vehicle. The control and guidance based path following for those tasks are described in this work. A standard sliding mode for controller design is briefly given. The method provides robust motion control efforts for an underwater vehicle’s decoupled system whilst minimising chattering effects. In a guidance system, the vector field based on a conventional artificial potential field method gives a desired trajectory with a use of existing information from sensors in the network. A well structured Line-of-Sight method is used for an AUV to follow the path. It provides guidance for an AUV to follow the predefined trajectory to a required position with the final desired orientation at the dock. Integration of a control and guidance system provides a complete system for this application. Simulation studies are illustrated in the paper

    Navigation Control of an Automated Guided Underwater Robot using Neural Network Technique

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    In recent years, under water robots play an important role in various under water operations. There is an increase in research in this area because of the application of autonomous underwater robots in several issues like exploring under water environment and resource, doing scientific and military tasks under water. We need good maneuvering capabilities and a well precision for moving in a specified track in these applications. However, control of these under water bots become very difficult due to the highly non-linear and dynamic characteristics of the underwater world. The logical answer to this problem is the application of non-linear controllers. As neural networks (NNs) are characterized by flexibility and an aptitude for dealing with non-linear problems, they are envisaged to be beneficial when used on underwater robots. In this research our artificial intelligence system is based on neural network model for navigation of an Automated Underwater robot in unpredictable and imprecise environment. Thus the back propagation algorithm has been used for the steering analysis of the underwater robot when it is encountered by a left, right and front as well as top obstacle. After training the neural network the neural network pattern was used in the controller of the underwater robot. The simulation of underwater robot under various obstacle conditions are shown using MATLAB

    Characteristic analysis and fluctuation control for a underactuated spherical underwater robot

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    With robots used widely in many fields in recent years, the underwater robot with various characteristics has been thoroughly researched. As a new type of underwater spherical robot, BYSQ-2 uses the heavy pendulum to adjust the attitude, which is flexible and novel. However, it has been not fully understood that how the heavy pendulum would affect the underactuated robot’s regular movement. In this paper a fluctuation characteristic for the robot is shown, and then an adaptive control method is proposed to suppress the fluctuation. Based on the simplified structure of the robot, a swing phenomenon of the heavy pendulum is found. Moreover, the reason for the fluctuation is analyzed in the processes of the accelerating and pitching. A dynamic equation for this model is established to accurately calculate the characteristic, and the virtual simulation proves the validity of the theoretical calculation. The characteristics of this coupling fluctuation are summarized by changing motion parameters and structure parameters. The results prove that the pendulum’s length and the controlling process are closely related with the velocity fluctuation of the robot. Moreover, in order to suppress the fluctuations, a pitching controller is designed to prevent the heavy pendulum from swinging based on the method of neural network sliding mode. The RBF neural network is used to compensate the nonlinearity and disturbance uncertainties, and two sliding mode structures make the swing rapidly inhibited. At the same time, the pitch angle's error also got convergence. The stability of the control system is proof by Lyapunov and Barbalat theories. Finally, the simulation and experiment show that the control method is feasible and excellent, which can fulfill the suppressed control for the fluctuation of the robot

    Effect of Communication Delays on the Successful Coordination of a Group of Biomimetic AUVs

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    In this paper, the influence of delays on the ability of a formation control algorithm to coordinate a group of twelve Biomimetic Autonomous Underwater Vehicles (BAUVs) is investigated. In this study the formation control algorithm is a decentralized methodology based on the behavioural mechanisms of fish within school structures. Incorporated within this algorithm is a representation of the well-known and frequently used communication protocol, Time-Division-Multiple-Access (TDMA). TDMA operates by assigning each vehicle a specific timeslot during which it can broadcast to the remaining members of the group. The size of this timeslot varies depending on a number of operational parameters such as the size of the message being transmitted, the hardware used and the distance between neighbouring vehicles. Therefore, in this work, numerous timeslot sizes are tested that range from theoretical possible values through to values used in practice. The formation control algorithm and the TDMA protocol have been implemented within a validated mathematical of the RoboSalmon BAUV designed and manufactured at the University of Glasgow. The results demonstrate a significant deterioration in the ability of the formation control algorithms as the timeslot size is increased. This deterioration is due to the fact that as the timeslot size is increased, the interim period between successive communication updates increases and as a result, the error between where the formation control algorithm estimates each vehicle to be and where they actually are, increases. As a result, since the algorithm no longer has an accurate representation of the positioning of neighbouring vehicles, it is no longer capable of selecting the correct behavioural equation and subsequently, is unable to coordinate the vehicles to form a stable group structure
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