AUV reactive planning: deepest point

Pang, Shuo; Farrell, Jay A.; Arrieta, Richard; Li, W.

doi:10.1109/oceans.2003.178246

Cited by 9 publications

(8 citation statements)

References 9 publications

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“…In a group scenario, loss of a (small) number of AUVs doesn't necessarily preclude the achievement of mission goals. Lastly, if each of the group AUVs are furnished with adaptive-sampling algorithms, such as in the chemical plume-tracing applications (Farrell et al, 2005;Pang, 2006;Pang et al, 2003), deployment of multiple vehicles guarantees much faster convergence to the points of interest. Cooperative control frameworks are split into centralized and decentralized strategies.…”

Section: The Cooperative Paradigmmentioning

confidence: 99%

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Formation Guidance of AUVs Using Decentralized Control Functions

Barisic¹,

Vukić²,

Mišković³

2011

Autonomous Underwater Vehicles

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Section: The Cooperative Paradigmmentioning

confidence: 99%

“…• Marine biology, conservationist biology, marine ecology management, biological oceanography (Farrell et al, 2005;Pang, 2006;Pang et al, 2003),…”

Section: Introductionmentioning

confidence: 99%

Formation Guidance of AUVs Using Decentralized Control Functions

Barisic¹,

Vukić²,

Mišković³

2011

Autonomous Underwater Vehicles

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“…If behaviors are added [3], they are only to cope with possible changes that are known a-priori by the operator. All this, therefore, leaves the platforms in isolation and limits the potential of multiple coordinated actions between adaptive collaborative agents.…”

Section: B Related Workmentioning

confidence: 99%

Interoperability of agent capabilities for autonomous knowledge acquisition and decision making in unmanned platforms

2009

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Robotic platforms are helping marine applications to gain routine and permanent access to the underwater environment. However, challenges related to this domain require the development and integration of more evolved embedded tools that can raise the platform's autonomy levels while maintaining the trust of the operator. This paper shows how knowledge representation, reasoning and planning tools can provide the required interoperability between embedded agents to achieve high-level mission goals described by the operator.

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“…However, these can be (and have been) combined in hybrid approaches (e.g., [28]). We will not discuss these but focus instead on the "homogeneous" groups that we identified.…”

Section: Sensor-based Techniques For Autonomous Underwater Vehiclesmentioning

confidence: 99%

Sensor-based problems and techniques for Autonomous Underwater Vehicles

Maciel

Sousa

2009

Oceans 2009-Europe

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We examine several problems and solutions that use active sensing and Autonomous Underwater Vehicles (AUVs). We are particularly interested in the multiple vehicles approaches or possibilities.We discuss and formulate different types of problems. These types are then classified in an original fashion, using activities (i.e., functionalities). Various limitations exist when using AUVs and underwater technologies to tackle the kinds of problems considered. We consider not only sampling issues and communication restrictions but also motion and sensing limitations. Techniques that have been proposed are then outlined. We analyze the approach, results, advantages and disadvantages and their multiple vehicles extension(s) and/or potential.The proposed classification scheme provides an informative way for structuring sensor-based problems for AUVs. The discussions on limitations and techniques allowed the identification of a problem and technique that can benefit from an expansion to multiple vehicles.

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AUV reactive planning: deepest point

Cited by 9 publications

References 9 publications

Formation Guidance of AUVs Using Decentralized Control Functions

Formation Guidance of AUVs Using Decentralized Control Functions

Interoperability of agent capabilities for autonomous knowledge acquisition and decision making in unmanned platforms

Sensor-based problems and techniques for Autonomous Underwater Vehicles

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