Decision system for a team of autonomous underwater vehicles—Preliminary report

Praczyk, Tomasz; Szymak, Piotr

doi:10.1016/j.neucom.2011.05.013

Cited by 20 publications

(26 citation statements)

References 10 publications

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“…Assembler Encoding with Evolvable Operations (AEEO) originates from a generative neuro-evolutionary method called Assembler Encoding (AE) [16,17]. In AE, an artificial neural network (ANN) is represented in the form of a linear program consisting of operations with predefined implementations and data.…”

Section: The Methods Used To Train Neural Network -Assembler Encodingmentioning

confidence: 99%

Using evolutionary neural networks to predict spatial orientation of a ship

Praczyk

2015

Neurocomputing

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Section: The Methods Used To Train Neural Network -Assembler Encodingmentioning

confidence: 99%

Using evolutionary neural networks to predict spatial orientation of a ship

Praczyk

2015

Neurocomputing

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“…Assembler encoding with evolvable operations (AEEO) originates from a generative neuro-evolutionary method called assembler encoding (AE) (Praczyk and Szymak 2011). In AE, an ANN is represented in the form of a linear program consisting of operations with predefined implementations and data.…”

Section: Assembler Encoding With Evolvable Operationsmentioning

confidence: 99%

Neural collision avoidance system for biomimetic autonomous underwater vehicle

Praczyk

2019

Soft Comput

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Autonomous underwater vehicles (AUVs) are underwater robots which are able to perform certain tasks without the help of a human operator. The key skill of each AUV is the capability to avoid collisions. To this end, appropriate devices and software are necessary with the potential to detect obstacles and to take proper decisions from the point of view of both the task and safety of the vehicle. The paper presents a neural collision avoidance system (NCAS) designed for the biomimetic autonomous underwater vehicle (BAUV). The NCAS is a component of the path following and collision avoidance system (PFCAS), which as the name implies is responsible for safely leading the vehicle along a desired path with collision avoidance. The task of NCAS is to make decisions regarding vehicle maneuvers in the horizontal plane, but only in the close proximity of the obstacles. It is implemented as an evolutionary artificial neural network designed by means of a neuro-evolutionary technique called assembler encoding with evolvable operations (AEEO). The paper outlines operation and construction of the BAUV as well as the PFCAS, the role of the NCAS in the entire system, and briefly presents AEEO as well as reporting on the experiments performed in simulation.

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“…The last 6 th section includes a summary of the research. Detailed description of the classical TSK system for anti-collision problem is presented in [15,17], and control-oriented model of the motion used for the USV is the same, which was applied for an underwater vehicle (UV) [13]. The motion of UV is considered in 6 degrees of freedom, while the motion of USV usually in 3 degrees of freedom.…”

Section: Fig 2 Mobile Control Centre Of Usv Edredonmentioning

confidence: 99%

“…To simulate horizontal plane motion of the USV and other vessels control-oriented model of marine object was applied [13]. The model was described in the following matrix form:…”

Section: Numerical Research Model Of the Vessel Motionmentioning

confidence: 99%