The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Marc Carreras - One of the best experts on this subject based on the ideXlab platform.
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online view planning for inspecting unexplored Underwater Structures
International Conference on Robotics and Automation, 2017Co-Authors: Eduard Vidal, Juan David Hernandez, Klemen Istenic, Marc CarrerasAbstract:In this letter, we propose a method to automate the exploration of unknown Underwater Structures for autonomous Underwater vehicles (AUVs). The proposed algorithm iteratively incorporates exteroceptive sensor data and replans the next-best-view in order to fully map an Underwater structure. This approach does not require prior environment information. However, a safe exploration depth and the exploration area (defined by a bounding box, parameterized by its size, location, and resolution) must be provided by the user. The algorithm operates online by iteratively conducting the following three tasks: 1) Profiling sonar data are first incorporated into a 2-D grid map, where voxels are labeled according to their state (a voxel can be labeled as empty, unseen, occluded, occplane, occupied, or viewed). 2) Useful viewpoints to continue exploration are generated according to the map. 3) A safe path is generated to guide the robot toward the next viewpoint location. Two sensors are used in this approach: a scanning profiling sonar, which is used to build an occupancy map of the surroundings, and an optical camera, which acquires optical data of the scene. Finally, in order to demonstrate the feasibility of our approach, we provide real-world results using the Sparus II AUV.
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coverage path planning with real time replanning and surface reconstruction for inspection of three dimensional Underwater Structures using autonomous Underwater vehicles
Journal of Field Robotics, 2015Co-Authors: Enric Galceran, David Ribas, Marc Carreras, Ricard Campos, Narcis Palomeras, Pere RidaoAbstract:We present a novel method for planning coverage paths for inspecting complex Structures on the ocean floor using an autonomous Underwater vehicle AUV. Our method initially uses a 2.5-dimensional 2.5D prior bathymetric map to plan a nominal coverage path that allows the AUV to pass its sensors over all points on the target area. The nominal path uses a standard mowing-the-lawn pattern in effectively planar regions, while in regions with substantial 3D relief it follows horizontal contours of the terrain at a given offset distance. We then go beyond previous approaches in the literature by considering the vehicle's state uncertainty rather than relying on the unrealistic assumption of an idealized path execution. Toward that end, we present a replanning algorithm based on a stochastic trajectory optimization that reshapes the nominal path to cope with the actual target structure perceived in situ. The replanning algorithm runs onboard the AUV in real time during the inspection mission, adapting the path according to the measurements provided by the vehicle's range-sensing sonars. Furthermore, we propose a pipeline of state-of-the-art surface reconstruction techniques we apply to the data acquired by the AUV to obtain 3D models of the inspected Structures that show the benefits of our planning method for 3D mapping. We demonstrate the efficacy of our method in experiments at sea using the GIRONA 500 AUV, where we cover part of a breakwater structure in a harbor and an Underwater boulder rising from 40i¾?m up to 27i¾?m depth.
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two step gradient based reinforcement learning for Underwater robotics behavior learning
Robotics and Autonomous Systems, 2013Co-Authors: Andres Elfakdi, Marc CarrerasAbstract:This article proposes a field application of a Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot in a cable tracking task. The Ictineu Autonomous Underwater Vehicle (AUV) learns to perform a visual based cable tracking task in a two step learning process. First, a policy is computed by means of simulation where a hydrodynamic model of the vehicle simulates the cable following task. The identification procedure follows a specially designed Least Squares (LS) technique. Once the simulated results are accurate enough, in a second step, the learnt-in-simulation policy is transferred to the vehicle where the learning procedure continues in a real environment, improving the initial policy. The Natural Actor-Critic (NAC) algorithm has been selected to solve the problem. This Actor-Critic (AC) algorithm aims to take advantage of Policy Gradient (PG) and Value Function (VF) techniques for fast convergence. The work presented contains extensive real experimentation. The main objective of this work is to demonstrate the feasibility of RL techniques to learn autonomous Underwater tasks, the selection of a cable tracking task is motivated by an increasing industrial demand in a technology to survey and maintain Underwater Structures.
Koh Umenai - One of the best experts on this subject based on the ideXlab platform.
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dynamic characterizations of Underwater Structures using noncontact vibration tests based on nanosecond laser ablation in water evaluation of passive vibration suppression with damping materials
Journal of Vibration and Control, 2018Co-Authors: Naoki Hosoya, Itsuro Kajiwara, Koh Umenai, Shingo MaedaAbstract:Recently, the demand for higher performing Underwater Structures under diverse conditions has increased. Examples include improved precision and speed of the position control of robot manipulators....
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dynamic characterizations of Underwater Structures using non contact vibration test based on nanosecond laser ablation in water investigation of cavitation bubbles by visualizing shockwaves using the schlieren method
Journal of Vibration and Control, 2016Co-Authors: Naoki Hosoya, Itsuro Kajiwara, Koh UmenaiAbstract:A pulsed-laser ablation method for non-contact experimental vibration analysis of completely submerged Underwater Structures is proposed. Although impact testing with an impulse hammer is commonly ...
Harry H Asada - One of the best experts on this subject based on the ideXlab platform.
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a self stabilizing Underwater sub surface inspection robot using hydrodynamic ground effect
International Conference on Robotics and Automation, 2015Co-Authors: Sampriti Bhattacharyya, Harry H Asada, Michael S TriantafyllouAbstract:In this paper we present a unique self stabilizing ellipsoidal robot for inspection of Underwater Structures using the principles of ground effect. Underwater metal Structures - whether it is ship hulls or internals of a boiling water reactor - require subsurface inspection to detect internal cracks, hidden cavities and other structural damage. This is usually done with on-contact ultrasonic sensors, a slow process if the structure is not sufficiently smooth. However, ultrasound can also be used with a precisely controlled gap. Such precision is challenging relying solely on actuators for control. This paper exploits near surface hydrodynamics to self stabilize a body at a precise gap. Specifically we show how boundary layer and venturi effects combine to create a stable, zero force position at a very small distance from the surface - conceptually similar to air bearings sliders on hard disk drives. Below the stable point lift force dominates, while above it Venturi suction prevails, each bringing the body back to equilibrium. Limitations in the restoring force are considered in the stability analysis included in the paper. This self stabilization method opens a whole new door for non-contact subsurface inspection of Underwater Structures by autonomous vehicles as well as precision distance maintenance in Underwater environment. Here we present our initial analysis and preliminary experimental results for the method when used with an ellipsoidal robot.
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control of a compact tetherless rov for in contact inspection of complex Underwater Structures
Intelligent Robots and Systems, 2014Co-Authors: Sampriti Bhattacharyya, Harry H AsadaAbstract:Abstract— In this paper we present the dynamic modeling and control of EVIE (Ellipsoidal Vehicle for Inspection and Exploration), an Underwater surface contact ROV (Remotely Operated Vehicle) for inspection and exploration. Underwater surface inspection is a challenging and hazardous task that demands sophisticated automation – as in boiling water nuclear reactors, water pipeline, submarine hull and oil pipelines inspection. EVIE is inspired by its predecessor, the Omni Submersible, in its ellipsoidal, streamlined, and appendage free shape. The objective for the robot is to carry inspection sensors – magnetic, acoustics or visual – to determine cracks on submerged surfaces. Unlike a robot moving in a practically boundless fluid, contact forces complicate the dynamics by bringing in normal and frictional forces, both of which are highly non linear in nature. This makes the modeling much more challenging and the development of an integrated controller more difficult. In this paper we will discuss the preliminary design and hydrodynamic modeling of such a robot. We analyze in detail the controls for one of the many transitional states of this robot. Eventually all transitional states need to be integrated to develop a hybrid dynamical system which shall use a controller that can adapt to its different states.
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A compact, maneuverable, Underwater robot for direct inspection of nuclear power piping systems
2012 IEEE International Conference on Robotics and Automation, 2012Co-Authors: Anirban Mazumdar, Martin Lozano, Aaron Fittery, Harry H AsadaAbstract:There is an increasing need for the inspection of nuclear power plants worldwide. To access complex Underwater Structures and perform non-destructive evaluation, robots must be tetherless, compact, highly maneuverable, and have a smooth body shape with minimal appendages. A new water jet propulsion system using fluidic valves coupled with centrifugal pumps is developed for precision maneuvering. A hybrid control system that combines continuous pump regulation and discrete Pulse Width Modulation (PWM) of fluidic valves is proposed. This control scheme provides high accuracy, high bandwidth, and flexibility in maneuvering control. First, the functional requirements for nuclear power plant inspection are discussed, followed by the basic design concept of an inspection robot. Miniaturized Coanda-effect valves are designed and built based on CFD and mathematical analysis. The hybrid control system incorporating the pump/valve system is designed and tested. Experimental results illustrate that the hybrid control scheme holds substantial promise and is capable of very precise orientation control. Based on these, a full 4-DOF robot is designed, and its key components are described.
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the eyeball rov design and control of a spherical Underwater vehicle steered by an internal eccentric mass
International Conference on Robotics and Automation, 2011Co-Authors: Ian C Rust, Harry H AsadaAbstract:A Remotely Operated Vehicle (ROV) is developed for use in the inspection of Underwater Structures in hazardous environments. The vehicle presented can change orientation like an eyeball using a novel gimbal mechanism for moving an internal eccentric mass. Combined with a pair of thrusters, the Eyeball ROV can move in any direction with non-holonomic constraints. In this paper the design concept is presented first, followed by dynamic and hydrodynamic analysis. Due to poor open loop stability characteristics, stability augmentation is implemented using onboard sensors and was designed and tested in simulation. A physical proof-of-concept prototype is also presented.
Ioannis Rekleitis - One of the best experts on this subject based on the ideXlab platform.
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contour based reconstruction of Underwater Structures using sonar visual inertial and depth sensor
Intelligent Robots and Systems, 2019Co-Authors: Sharmin Rahman, Ioannis RekleitisAbstract:This paper presents a systematic approach on realtime reconstruction of an Underwater environment using Sonar, Visual, Inertial, and Depth data. In particular, low lighting conditions, or even complete absence of natural light inside caves, results in strong lighting variations, e.g., the cone of the artificial video light intersecting Underwater Structures, and the shadow contours. The proposed method utilizes the well defined edges between well lit areas and darkness to provide additional features, resulting into a denser 3D point cloud than the usual point clouds from a visual odometry system. Experimental results in an Underwater cave at Ginnie Springs, FL, with a custom-made Underwater sensor suite demonstrate the performance of our system. This will enable more robust navigation of autonomous Underwater vehicles using the denser 3D point cloud to detect obstacles and achieve higher resolution reconstructions.
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sonar visual inertial slam of Underwater Structures
International Conference on Robotics and Automation, 2018Co-Authors: Sharmin Rahman, Ioannis RekleitisAbstract:This paper presents an extension to a state of the art Visual-Inertial state estimation package (OKVIS) in order to accommodate data from an Underwater acoustic sensor. Mapping Underwater Structures is important in several fields, such as marine archaeology, search and rescue, resource management, hydrogeology, and speleology. Collecting the data, however, is a challenging, dangerous, and exhausting task. The Underwater domain presents unique challenges in the quality of the visual data available; as such, augmenting the exteroceptive sensing with acoustic range data results in improved reconstructions of the Underwater Structures. Experimental results from Underwater wrecks, an Underwater cave, and a submerged bus demonstrate the performance of our approach.
Seonghun Hong - One of the best experts on this subject based on the ideXlab platform.
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Selective image registration for efficient visual SLAM on planar surface Structures in Underwater environment
Autonomous Robots, 2019Co-Authors: Seonghun HongAbstract:This paper presents a computationally efficient approach that can be applied to visual simultaneous localization and mapping (SLAM) for the autonomous inspection of Underwater Structures using monocular vision. A selective image registration scheme consisting of key-frame selection and key-pair selection is proposed to effectively use visual features that may not be evenly distributed on the surface of Underwater Structures. The computational cost of the visual SLAM algorithm can be substantially reduced using only potentially effective images and image pairs by applying the proposed image registration scheme. The performance of the proposed approach is demonstrated on two different experimental datasets obtained using autonomous Underwater vehicles.
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efficient visual slam using selective image registration for autonomous inspection of Underwater Structures
IEEE OES Autonomous Underwater Vehicles, 2016Co-Authors: Seonghun Hong, Jinwhan KimAbstract:Visual inspection of Underwater Structures including ship-hull inspection has been performed by human divers. It is a highly dangerous task and thus can be a potential application for unmanned Underwater vehicles. This paper introduces an efficient visual simultaneous localization and mapping (SLAM) algorithm that can be applied to the autonomous inspection of Underwater Structures. Considering that visual features are sparsely located on the surface of typical Underwater Structures, the proposed visual SLAM algorithm employs a selective image registration scheme consisting of key-frame selection and key-pair selection. By using only potentially effective images and image pairs for feature-based image registration, the computational burden of the visual SLAM can be substantially reduced, compared with the conventional method. Experimental results using a hover-capable unmanned Underwater vehicle verify the practical feasibility and performance of the proposed methodology.
