Target Localization and Autonomous Navigation Using Wireless Sensor Networks—A Pseudogradient Algorithm Approach

Deshpande, Nikhil; Grant, Edward; Henderson, Thomas C.

doi:10.1109/jsyst.2013.2260631

Cited by 52 publications

(24 citation statements)

References 19 publications

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“…The sensor nodes do not entail anchor nodes. Hence, the algorithm provides node positions that imply the location of the sensor nodes relative to each other [2].…”

Section: Anchor Free Localization Algorithmmentioning

confidence: 99%

“…For many ranging systems, the distance measurement is much less than that of communication ranges [2]. The accuracy for estimating the localization declines rapidly due to the lack of anchor nodes [47].…”

Section: Based On Node Density 91 Sparse Localization Algorithmmentioning

confidence: 99%

“…The power unit is responsible for supplying node energy. Small batteries or capacitors are equipped in the sensor nodes to produce small-sized and low-cost devices [2].…”

Section: Introductionmentioning

confidence: 99%

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Retrospection on Localization Techniques for Positioning Nodes in Wireless Sensor Networks

Kathiroli¹,

Kanmani²

2020

IJEAT

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Wireless Sensor Networks have highly scattered, self-organized nodes that can detect, compute, and transmit the information collected at different nodes in the network. These nodes spread over a specific topographical zone. They enhance the instantaneous formation of the network. Knowing the current location of a node is a crucial and cardinal requirement for any application promulgated in WSN. Once the locations of the sensor nodes can be precisely positioned, there are ample of probabilities for the data transmission of the network to be excelling inefficiency. Location responsiveness enables essential network features such as coverage, routing, deployment, topology control, clustering, boundary discovery, target tracking, rescue, and other location services. Hence, WSN localization has become a breath and backbone arena that ostentatiously attracted significant research interest. Our work traces a compilation of all the dynamic research in sensor networks on localization techniques and emanates eminent understanding of it.

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“…The sensor nodes do not entail anchor nodes. Hence, the algorithm provides node positions that imply the location of the sensor nodes relative to each other [2].…”

Section: Anchor Free Localization Algorithmmentioning

confidence: 99%

Section: Based On Node Density 91 Sparse Localization Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Retrospection on Localization Techniques for Positioning Nodes in Wireless Sensor Networks

Kathiroli¹,

Kanmani²

2020

IJEAT

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“…The general conditions of the mobile robot working environment is complex, and some areas are not even suitable for human to stay, so in order to ensure that the robot can successfully complete the task, the operator needs to control the real-time location of their work [1]. Therefore, the mobile robot needs to be tracked and positioned during operation.…”

Section: Introductionmentioning

confidence: 99%

An Algorithm of Mobile Robot Node Location Based on Wireless Sensor Network

2017

Int. J. Onl. Eng.

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Abstract-In the wireless sensor network, there is a consistent one-to-one match between the information collected by the node and the location of the node. Therefore, it attempts to determine the location of unknown nodes for wireless sensor networks. At present, there are many kinds of node localization methods. Because of the distance error, hardware level, application environment and application costs and other factors, the positioning accuracy of various node positioning methods is not in complete accord. The objective function is established and algorithm simulation experiments are carried out to make a mobile ronot node localization. The experimnettal results showed that the proposed algorithm can achieve higher localization precision in fewer nodes. In addition, the localization algorithm was compared with the classical localization algorithm. In conclusion, it is verified that the localization algorithm proposed in this paper has higher localization accuracy than the traditional classical localization algorithm when the number of nodes is larger than a certain number.

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“…As for positioning or localization [6][7][8][9][10][11][12][13][14][32][33][34][35] and path planning [15][16][23][24][25][26], which are quite essential in transportation, different methods have been proposed. There are some techniques of localization (e.g., the global positioning system, wheeled odometry [8], ultrasound localization [9], visual odometry [10][11][12], map of environment, and multi-sensor fusing method [14]).…”

Section: Introductionmentioning

confidence: 99%

Integration of Hardware and Software Designs for Object Grasping and Transportation by A Mobile Robot With Navigation Guidance via a Unique and Elegant Design of Bearing Alignment Mechanism

Yue

2015

IEEE/ASME Trans. Mechatron.

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In this paper, we consider the systematic design and implementation of grasping and transportation by a mobile robot with low implementation complexity. The work is mainly divided into three aspects: 1) design of a mechanical gripper and an arm mounted on the robot for grasping; 2) design of the hardware communication configuration (HCC) for transportation guidance that includes a destination beacon and a sensor system on the robot that working together with some designed event-triggered communication mechanisms, the HCC is low-cost in the sense of low energy consumption; and 3) an effective and low-cost heuristic transportation algorithm that is perfectly and tightly incorporated with the designed HCC in an event-triggered manner and the unique design of bearing alignment mechanism. The particular contribution is the tight integration of the heuristic software algorithm and the HCC, and the very simple nature of the transportation algorithm dues to this integration, which passes some computational functions to the HCC. Numerical simulations and experiments are presented, showing the effectiveness of the proposed system.

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Target Localization and Autonomous Navigation Using Wireless Sensor Networks—A Pseudogradient Algorithm Approach

Cited by 52 publications

References 19 publications

Retrospection on Localization Techniques for Positioning Nodes in Wireless Sensor Networks

Retrospection on Localization Techniques for Positioning Nodes in Wireless Sensor Networks

An Algorithm of Mobile Robot Node Location Based on Wireless Sensor Network

Integration of Hardware and Software Designs for Object Grasping and Transportation by A Mobile Robot With Navigation Guidance via a Unique and Elegant Design of Bearing Alignment Mechanism

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