Energy Consumption Research of Mobile Data Collection Protocol for Underwater Nodes Using an USV

Lv, Zhichao; Zhang, Jie; Jin, Jiucai; Li, Qi; Gao, Baoru

doi:10.3390/s18041211

Cited by 9 publications

(3 citation statements)

References 15 publications

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“…Avoiding unpredictable obstacles can better solve the DWA [28]. DWA is widely used in dynamic obstacle avoidance path optimization of UAVs, robots, and USVs [29][30][31]. Dobrevski reported local path planning based on DWA and deep reinforcement learning to improve path optimization [32].…”

Section: Introductionmentioning

confidence: 99%

Optimized Dynamic Collision Avoidance Algorithm for USV Path Planning

Zhu

2023

Sensors

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Ship collision avoidance is a complex process that is influenced by numerous factors. In this study, we propose a novel method called the Optimal Collision Avoidance Point (OCAP) for unmanned surface vehicles (USVs) to determine when to take appropriate actions to avoid collisions. The approach combines a model that accounts for the two degrees of freedom in USV dynamics with a velocity obstacle method for obstacle detection and avoidance. The method calculates the change in the USV’s navigation state based on the critical condition of collision avoidance. First, the coordinates of the optimal collision avoidance point in the current ship encounter state are calculated based on the relative velocities and kinematic parameters of the USV and obstacles. Then, the increments of the vessel’s linear velocity and heading angle that can reach the optimal collision avoidance point are set as a constraint for dynamic window sampling. Finally, the algorithm evaluates the probabilities of collision hazards for trajectories that satisfy the critical condition and uses the resulting collision avoidance probability value as a criterion for course assessment. The resulting collision avoidance algorithm is optimized for USV maneuverability and is capable of handling multiple moving obstacles in real-time. Experimental results show that the OCAP algorithm has higher and more robust path-finding efficiency than the other two algorithms when the dynamic obstacle density is higher.

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Section: Introductionmentioning

confidence: 99%

Optimized Dynamic Collision Avoidance Algorithm for USV Path Planning

Zhu

2023

Sensors

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“…), etc. [7]- [14] The definition of the command center is a structure planning the execution mode of operations and actions. A command center can have one or more work points; thus, a working point is closer to the location of the action.…”

Section: Drones/surface Platforms 21 Introductory Notes Overviewmentioning

confidence: 99%

State of the Art - Drones/Surface Platforms and Green Energy

Popa,

Popescu,

Mocanu

2023

IOP Conf. Ser.: Earth Environ. Sci.

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This paper presents a summary of what surface drones mean and the possibility of using these platforms in pollution problems. Also, in this paper, the authors have proposed to predict (in the form of a review) the possibility of producing the electricity needed for these platforms with the help of photovoltaic panels and the storage of energy in different types of batteries. This paper is a summary of what drones/surface platforms entail, the production of electricity using photovoltaic panels and an overview of battery types.

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“…Wireless maneuvering control functions, such forward and backward motion or turning in place, are realized through a universal synchronous/asynchronous receiver/transmitter (USART) and a universal serial bus (USB) cable [20], where the control system downloads target files to a custom-made master board to facilitate maneuvering control [21], [22]. The controller program designed to manipulate the USCV remotely according to the three operational modes offers the beneficial features of high-speed response and reliable wireless communication [23]- [25]. The propulsion system achieves articulated USCV motion by employing two submerged pumps as water jet generators [26], with six magnetic valves as the jet controllers.…”

mentioning

confidence: 99%

Control System Design and Thrust Analysis of an Unmanned Surface Cleaning Vessel With a Novel Pump-Valve Propulsion System

Luo

Zheng

et al. 2020

IEEE Access

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This article presents a specialized control system for an unmanned surface cleaning vessel (USCV) employing a pump-valve propulsion system. The system has three operational modes, including manual remote-control mode, self-automated cruise mode, and self-locking remote-control mode. In the manual remote-control mode, users remotely control the vessel by means of a motion-control joystick. In the self-automated cruise mode, the control system is capable of detecting obstacles and automatically controlling the pump-valve propulsion system in response to feedback signals from sensors. The selflocking remote-control mode functions similarly to the first mode, except that the joystick controls the vessel motion in accordance with a single established joystick-actuation pattern. The control system is supported by a commercially available remote controller with wireless communication technology. The functionality of the combined control and pump-valve propulsion system is verified by computational fluid dynamics simulations and experimental tests conducted using a prototype USCV. The combined control and pumpvalve propulsion system is demonstrated to be a cost-effective, simple, and innovative platform that is suitable for use with USCVs. INDEX TERMS USCV, pump-valve propulsion, operational modes, CFD, motion states.

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Energy Consumption Research of Mobile Data Collection Protocol for Underwater Nodes Using an USV

Cited by 9 publications

References 15 publications

Optimized Dynamic Collision Avoidance Algorithm for USV Path Planning

Optimized Dynamic Collision Avoidance Algorithm for USV Path Planning

State of the Art - Drones/Surface Platforms and Green Energy

Control System Design and Thrust Analysis of an Unmanned Surface Cleaning Vessel With a Novel Pump-Valve Propulsion System

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