Recent trends in control architectures for autonomous underwater vehicles

Ridao, Pere; Batlle, Joan; Amat, Josep; Roberts, G.N.

doi:10.1080/002077299291895

Cited by 58 publications

(29 citation statements)

References 17 publications

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“…수중 무인 잠수정을 위해서 다양한 자율제어 구조가 연 구되어 왔다 [6][7][8][9] . 현재 개발 중인 PETASUS 시스템 II의 제 어 시스템은 한종희 등 일반적으로 상위 레벨 제어기에는 기능적으로 계획 기 술, 판단 기술, 지능 등이 고려되어야 한다 [8] .…”

Section: 제어 시스템unclassified

Localization and Autonomous Control of PETASUS System II for Manipulation in Structured Environment

Han¹,

Ok²,

Chung³

2013

The Journal of Korea Robotics Society

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In this paper, a localization algorithm and an autonomous controller for PETASUS system II which is an underwater vehicle-manipulator system, are proposed. To estimate its position and to identify manipulation targets in a structured environment, a multi-rate extended Kalman filter is developed, where map information and data from inertial sensors, sonar sensors, and vision sensors are used. In addition, a three layered control structure is proposed as a controller for autonomy. By this controller, PETASUS system II is able to generate waypoints and make decisions on its own behaviors. Experiment results are provided for verifying proposed algorithms.

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Section: 제어 시스템unclassified

Localization and Autonomous Control of PETASUS System II for Manipulation in Structured Environment

Han¹,

Ok²,

Chung³

2013

The Journal of Korea Robotics Society

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“…At this level, the mission executive follows a sequence of basic command primitives and issues them to the functional control layer of the platform. Description about how these approaches maintain control of underwater vehicles can be found in Fossen (1994), Ridao et al (1999) and Yuh (2000). In this situation, decisions taken by the operator are made using only orientation inputs related to some previous experience and a-priori knowledge.…”

Section: Unmanned Decision Making Loopmentioning

confidence: 99%

Embedded Knowledge and Autonomous Planning: The Path Towards Permanent Presence of Underwater Networks

Patrón¹,

Miguelanez²,

Pétillot³

2011

Autonomous Underwater Vehicles

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“…he current state of the art in UUV control consists of three different types of architectures: deliberative, behavioral and hybrid architectures [3]. Deliberative architecture is also known as hierarchical architecture, which is based on the world model.…”

Section: Uuv Control Architecturementioning

confidence: 99%

A semi-physical simulation framework for multiple unmanned underwater vehicles

Ren

Tan

et al. 2010

2010 Chinese Control and Decision Conference

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A semi-physical simulation framework for multiple unmanned underwater vehicles' (UUVs) coordinate operation, which can complete large-scale reconnaissance in civil, academic military application, is presented. The structure of simulation framework consists of virtual environment unit, vision display unit and UUV control unit. The primary motivation of this simulation framework is test the UUV control unit in order to transplant the control unit in real UUV fleetly and reliably. The software architecture of control unit which is based on multi-agent system, consists of coordination layer, task layer, behavior layer and physical layer, is developed in real-time operation system VxWorks. The significant power of the semi-physical simulation framework is provide a platform to validate the coordinate operation and control strategy of UUV in dynamic environment, and the maturity and stability of the entire control system.

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Recent trends in control architectures for autonomous underwater vehicles

Cited by 58 publications

References 17 publications

Localization and Autonomous Control of PETASUS System II for Manipulation in Structured Environment

Localization and Autonomous Control of PETASUS System II for Manipulation in Structured Environment

Embedded Knowledge and Autonomous Planning: The Path Towards Permanent Presence of Underwater Networks

A semi-physical simulation framework for multiple unmanned underwater vehicles

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