Robust underwater obstacle detection and collision avoidance

Ganesan, Varadarajan; Brekke, Edmund

doi:10.1007/s10514-015-9532-2

Cited by 18 publications

(9 citation statements)

References 26 publications

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“…Since the proposed underwater navigation rules in this article are based on a grid occupancy method, review of other CAS methods, such as image processing techniques and simultaneous localization and mapping (SLAM), are deemed to be out of the scope of this article. The grid occupancy method is chosen for two main reasons: first, as observed by Ganesan et al, (2016)…”

Section: Collision Avoidance Methods For Autonomous Underwater Vehiclesmentioning

confidence: 99%

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Development of safety envelopes and subsea traffic rules for autonomous remotely operated vehicles

Hegde

Henriksen

Utne

et al. 2019

Journal of Loss Prevention in the Process Industries

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This article presents the process used to develop safety envelopes and subsea traffic rules for autonomous remotely operated vehicles (AROVs) used in subsea inspection, maintenance, and repair (IMR) operations. Preventing loss of subsea assets and the AROV is the overall goal of the proposed safety envelopes and subsea traffic rules. Currently, no such envelopes and rules exist. The safety envelope for the AROV is constructed using an Octree method. The proposed subsea traffic rules are derived by combining existing traffic regulations in marine and aviation industries. The proposed safety envelopes and traffic rules are tested using both a novel modular open robot simulation engine (MORSE) based underwater simulator and in the laboratory. The results from the laboratory tests show that the proposed safety envelopes and subsea traffic rules can be used during simulated or real IMR operations to recommend subsea traffic rules to the AROV and the human supervisor.

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Section: Collision Avoidance Methods For Autonomous Underwater Vehiclesmentioning

confidence: 99%

“…No No Ganesan et al, (2016) Present an obstacle detection and avoidance algorithm for AUVs using a local occupancy grid on an AUV frame and probabilistic approaches to avoid false alarms and noise/clutter in the sonar data. The obstacles are detected in the AUV local occupancy grid.…”

Section: Collision Avoidance Methods For Autonomous Underwater Vehiclesmentioning

confidence: 99%

Development of safety envelopes and subsea traffic rules for autonomous remotely operated vehicles

Hegde

Henriksen

Utne

et al. 2019

Journal of Loss Prevention in the Process Industries

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“…Therefore, many aspects of an AUV deployment had been examined in parts, both spatially and temporally, in an attempt to control the risk of loss. Most risk analysis approaches focused on technical aspects of AUVs to improve robustness and reliabilities in areas such as; the mission management software, navigation system, collision avoidance system, emergency abort system, power system, homing system and communication system (2)(3)(4)(5)(6)(7)(8)(9)(10)(11) . As AUV technology gradually made the transition from research and development to operations, proactive and systematic risk analysis approaches based primarily on historical performance data of the AUV (12)(13)(14) emerges.…”

Section: Risk Analysis Of Auv Deploymentmentioning

confidence: 99%

A Hybrid Fuzzy System Dynamics Approach for Risk Analysis of AUV Operations

Loh¹,

Brito²,

Bose³

et al. 2020

JACIII

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The maturing of autonomous technology has fostered a rapid expansion in the use of Autonomous Underwater Vehicles (AUVs). To prevent the loss of AUVs during deployments, existing risk analysis approaches tend to focus on technicalities, historical data and experts’ opinion for probability quantification. However, data may not always be available and the complex interrelationships between risk factors are often neglected due to uncertainties. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. The approach utilises the strengths while overcoming limitations of both system dynamics and fuzzy set theory. Presented as a three-step iterative framework, the approach was applied on a case study to examine the impact of crew operating experience on the risk of AUV loss. Results showed not only that initial experience of the team affects the risk of loss, but any loss of experience in earlier stages of the AUV program have a lesser impact as compared to later stages. A series of risk control policies were recommended based on the results. The case study demonstrated how the FuSDRA approach can be applied to inform human resource and risk management strategies, or broader application within the AUV domain and other complex technological systems.

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“…In literature 34 the fusion of Multi-beam and Sector Scanning Sonars is proposed. Sector Scanners provides a set of scan lines by mechanically moving the unit to obtain an image, hence some image compensation would be required to produce an accurate image.…”

Section: Obstacle Detection Sensorsmentioning

confidence: 99%

A review of the technological developments for interlocking at level crossing

Fayyaz

Alexoulis-Chrysovergis

Southgate

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part F:

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A Level Crossing remains as one of the highest risk assets within the railway system often depending on the unpredictable behaviour of road and footpath users. For this purpose, interlocking through automated safety systems remains a key area for investigation. Within Europe, 2015–2016, 469 accidents at crossings were recorded of which 288 lead to fatalities and 264 lead to injuries. The European Union’s Agency for Railways has reported that Level Crossing fatalities account for just under 28% of all railway fatalities. This paper identifies suitable obstacle detection technologies and their associated algorithms that can be used to support risk reduction and management of Level Crossings. Furthermore, assessment and decision methods are presented to support their application. Finally state of the art and synergistic opportunity of which a combination of obstacle detection sensors with intelligent decisions layers such as Deep Learning are discussed which can provide robust interlocking decisions for rail applications. The sensor fusion of video camera and RADAR is a promising solution for Level Crossings. By applying additional sensing techniques such as RADAR imaging, further capabilities are added to the system, which can lead to a more robust approach.

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Robust underwater obstacle detection and collision avoidance

Cited by 18 publications

References 26 publications

Development of safety envelopes and subsea traffic rules for autonomous remotely operated vehicles

Development of safety envelopes and subsea traffic rules for autonomous remotely operated vehicles

A Hybrid Fuzzy System Dynamics Approach for Risk Analysis of AUV Operations

A review of the technological developments for interlocking at level crossing

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