UUV Simulator: A Gazebo-based package for underwater intervention and multi-robot simulation

Manhães, Musa; Scherer, Sebastian; Voss, Martin; Douat, Luiz Ricardo; Rauschenbach, Thomas

doi:10.1109/oceans.2016.7761080

Cited by 196 publications

(99 citation statements)

References 9 publications

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“…They can simulate a wide variety of sensors, and support different physics engines. The UUV Simulator [16] is a plugin for Gazebo that allows underwater simulation. It extends the physics engine to simulate the rigid body dynamics underwater, as well as some typical underwater sensor models.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Generation and Processing of Simulated Underwater Images for Infrastructure Visual Inspection with UUVs

Álvarez-Tuñón

Jardón

Balaguer

2019

Sensors

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The development of computer vision algorithms for navigation or object detection is one of the key issues of underwater robotics. However, extracting features from underwater images is challenging due to the presence of lighting defects, which need to be counteracted. This requires good environmental knowledge, either as a dataset or as a physic model. The lack of available data, and the high variability of the conditions, makes difficult the development of robust enhancement algorithms. A framework for the development of underwater computer vision algorithms is presented, consisting of a method for underwater imaging simulation, and an image enhancement algorithm, both integrated in the open-source robotics simulator UUV Simulator. The imaging simulation is based on a novel combination of the scattering model and style transfer techniques. The use of style transfer allows a realistic simulation of different environments without any prior knowledge of them. Moreover, an enhancement algorithm that successfully performs a correction of the imaging defects in any given scenario for either the real or synthetic images has been developed. The proposed approach showcases then a novel framework for the development of underwater computer vision algorithms for SLAM, navigation, or object detection in UUVs.

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Section: Related Workmentioning

confidence: 99%

“…A similar problem occurs in simulation. The available open-source underwater simulators are UWSim (UnderWater Simulator) [15] and UUV (Unmanned Underwater Vehicle) Simulator [16]. UWSim allows for visualization of a virtual underwater scenario, as well as simulated sensors and a control interface for underwater vehicles.…”

Section: Introductionmentioning

confidence: 99%

Generation and Processing of Simulated Underwater Images for Infrastructure Visual Inspection with UUVs

Álvarez-Tuñón

Jardón

Balaguer

2019

Sensors

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“…Furthermore, real observed environment conditions, like camera image noise, haze or illumination, can be estimated to reflect similar conditions in simulation. For this, we rely on Gazebo's built-in sensor noise models, scene fog and lighting options as well as the UUV Simulator camera plugin [17]. Consequently, spatial and environment conditions perceived from real observations are continuously reflected in simulation in a cylic manner, as shown in Fig.…”

Section: Increasing Continuous System Integration Robustness Usinmentioning

confidence: 99%

“…light and color attenuation. The simulated stereo camera applies an exponential attenuation on the pixel intensity as described in [17]:…”

Section: A Environment Condition Adaptation (T E )mentioning

confidence: 99%

Robust Continuous System Integration for Critical Deep-Sea Robot Operations Using Knowledge-Enabled Simulation in the Loop

Mueller

Doernbach

Chavez

et al. 2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Deep-sea robot operations demand a high level of safety, efficiency and reliability. As a consequence, measures within the development stage have to be implemented to extensively evaluate and benchmark system components ranging from data acquisition, perception and localization to control. We present an approach based on high-fidelity simulation that embeds spatial and environmental conditions from recorded real-world data. This simulation in the loop (SIL) methodology allows for mitigating the discrepancy between simulation and real-world conditions, e.g. regarding sensor noise. As a result, this work provides a platform to thoroughly investigate and benchmark behaviors of system components concurrently under real and simulated conditions. The conducted evaluation shows the benefit of the proposed work in tasks related to perception and self-localization under changing spatial and environmental conditions.

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“…An Underwater Unmanned Vehicle (UUV) simulator [2] has been developed during the project. It is based on the 3D open source robotics simulator Gazebo and allows the simulation of environment and vehicle dynamics.…”

Section: F Implementationmentioning

confidence: 99%

A generic and modular architecture for maritime autonomous vehicles

Barbier

Bensana

Pucel

2018

2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV)

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Autonomous systems face the challenge of managing disruptive events such as internal alterations, mission updates and environmental perturbations that always occur in an operational context. Autonomous vehicles must embed the capabilities to supervise their behaviour and to detect and react to such events. The complexity increases with the heterogeneity of vehicles in the team and the communication constraints. This paper describes the Robot System Onboard Architecture (RSOA) software developed in the SWARMs project for the achievement of offshore maritime operations. This generic and modular architecture implements high level capabilities in a semiautonomous or autonomous manner, and is deployed at a lower level on a heterogeneous swarm of vehicles. Target vehicles include autonomous and teleoperated underwater vehicles, and surface vehicles. Simulation and experimentations achieved on the Black Sea in Romania (July 2017) then in the Trondheim fjord in Norway (June 2018) highlighted the good performance of the RSOA.

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UUV Simulator: A Gazebo-based package for underwater intervention and multi-robot simulation

Cited by 196 publications

References 9 publications

Generation and Processing of Simulated Underwater Images for Infrastructure Visual Inspection with UUVs

Generation and Processing of Simulated Underwater Images for Infrastructure Visual Inspection with UUVs

Robust Continuous System Integration for Critical Deep-Sea Robot Operations Using Knowledge-Enabled Simulation in the Loop

A generic and modular architecture for maritime autonomous vehicles

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