AUV's trends over the world in the future decade

Yong-kuan, Liang

doi:10.1109/auv.1992.225184

Cited by 10 publications

(3 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e French developed the world's first AUV, Epaulard, in the 1970s [1]. After more than 40 years of development, AUV has been widely used in marine environment exploration [2,3], marine mineral exploration [4], marine data collection [5], maritime alert [6], and other aspects.…”

Section: Introductionmentioning

confidence: 99%

An Embedded Linear Model Three-Dimensional Fuzzy PID Control System for a Bionic AUV under Wave Disturbance

Lyu

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

This study provides a new embedded linear model (ELM) three-dimensional fuzzy PID control method for a bionic autonomous underwater vehicle (AUV), which is disturbed by ocean waves. The uncertainty of the ocean waves will make it difficult for the AUV to achieve good sailing quality, especially near the sea surface. In view of this problem, an ELM fuzzy PID controller, which adopts three-dimensional fuzzy control rules, is designed. In the ELM fuzzy PID controller, a linear model of AUV is established in order to actively perceive the effect of waves on AUV. Hence, the wave disturbance can be reflected in the control signal earlier and faster. Finally, three simulations are carried out to verify the control effect of the ELM fuzzy PID controller. An ocean wave disturbance model is established in order to simulate the force and the moment acting on the AUV. The results imply that compared with the classical PID controller and normal fuzzy PID controller, the ELM fuzzy PID controller can significantly enhance the stability of AUV and make the response faster and overshoot smaller.

show abstract

Section: Introductionmentioning

confidence: 99%

An Embedded Linear Model Three-Dimensional Fuzzy PID Control System for a Bionic AUV under Wave Disturbance

Lyu

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…Underwater robotics poses substantial scientific challenges, especially with regard to autonomy in this field [Yongkuan (1992)]. Underwater exploration is of tremendous interest from the industrial as well as from the scientific perspective, let it be in shallow coastal waters or in the deep sea.…”

Section: Introductionmentioning

confidence: 99%

Fast Prototyping of an Autonomous Underwater Vehicle With the Cubesystem

Albu¹,

Birk²,

Dobrev³

et al. 2007

IFAC Proceedings Volumes

View full text Add to dashboard Cite

“…In the evolving field of AUVs, however, the more fundamental issues of power, propulsion, communications, and survival in a harsh environment have predominated (Dunn and Blidberg, 1989;Yongkuan, 1992). Although the issues of perception, scene reconstruction, and world modeling have also been addressed (e.g., Chantler and Reid, 1991;Rosenblum and Kamgar-Parsi, 1992;Cox and Leonard, 1994;Caccia et al 1995), much has been taken from terrestrial robotics, which does not consider the special problems of working underwater.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional stochastic modeling using sonar sensing for undersea robotics

Stewart

1996

Auton Robot

View full text Add to dashboard Cite

This paper describes an approach to the construction of three-dimensional stochastic models for intelligent systems exploring an underwater environment. Important characteristics shared by such applications are:(1) real-time constraints; (2) unstructured, three-dimensional terrain; (3) high-bandwidth sensors providing redundant, overlapping coverage; (4) lack of prior knowledge about the environment; and (5) inherent inaccuracy or ambiguity in sensing and interpretation. The paper develops an underlying theory of stochastic backprojection and demonstrates how such an approach satisfies these five needs for undersea robotics.Models are cast as three-dimensional spatial decompositions of stochastic feature vectors. A numerical approach to incorporating new sensor information is derived from an incremental adaptation of the summation method for image reconstruction. Error and ambiguity are accounted for by blurring a spatial projection of remote-sensor data before combining them stochastically with the model. By exploiting the redundancy in high-bandwidth sensing, model certainty and resolution are enhanced as more data accumulate. In the case of a three-dimensional profiling sonar, the model converges to a "fuzzy" surface distribution from which a deterministic surface map is extracted.To verify the fundamental properties of stochastic backprojection and the resulting models, computer simulations are used to demonstrate: impulse and ramp responses; mitigation of artifacts caused by deterministic processing; incremental increase in accuracy and reduction of uncertainty; and convergence. Two examples illustrate how this approach has been successfully applied in the field for three-dimensional modeling of a sunken shipwreck by a remote undersea vehicle and for backscatter modeling of undersea terrain.

show abstract

AUV's trends over the world in the future decade

Cited by 10 publications

References 82 publications

An Embedded Linear Model Three-Dimensional Fuzzy PID Control System for a Bionic AUV under Wave Disturbance

An Embedded Linear Model Three-Dimensional Fuzzy PID Control System for a Bionic AUV under Wave Disturbance

Fast Prototyping of an Autonomous Underwater Vehicle With the Cubesystem

Three-dimensional stochastic modeling using sonar sensing for undersea robotics

Contact Info

Product

Resources

About