An efficient approach for undelayed range-only SLAM based on Gaussian mixtures expectation

Fabresse, Felipe R.; Caballero, Fernando; Maza, Iván; Ollero, A.

doi:10.1016/j.robot.2018.02.014

Cited by 13 publications

(2 citation statements)

References 44 publications

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“…This distance measure may be nonlinear and can be linearized by Jacobian as [ 36 ] the gain of the Kalman filter is computed as [ 37 ] where is the variance of . In the correction phase, based on the gain of the Kalman filter and the last distance measure of the UE j from i.e., the state transition matrix and covariance matrix updated as …”

Section: The Proposed Localization Of Ground Ues and Their Associatio...mentioning

confidence: 99%

Q-learning-based UAV-mounted base station positioning in a disaster scenario for connectivity to the users located at unknown positions

Mandloi

Arya

2023

J Supercomput

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Due to its flexibility, cost-effectiveness, and quick deployment abilities, unmanned aerial vehicle-mounted base station (UmBS) deployment is a promising approach for restoring wireless services in areas devastated by natural disasters such as floods, thunderstorms, and tsunami strikes. However, the biggest challenges in the deployment process of UmBS are ground user equipment’s (UE’s) position information, UmBS transmit power optimization, and UE-UmBS association. In this article, we propose Localization of ground UEs and their Association with the UmBS (LUAU), an approach that ensures localization of ground UEs and energy-efficient deployment of UmBSs. Unlike existing studies that proposed their work based on the known UEs positional information, we first propose a three-dimensional range-based localization approach (3D-RBL) to estimate the position information of the ground UEs. Subsequently, an optimization problem is formulated to maximize the UE’s mean data rate by optimizing the UmBS transmit power and deployment locations while taking the interference from the surrounding UmBSs into consideration. To achieve the goal of the optimization problem, we utilize the exploration and exploitation abilities of the Q-learning framework. Simulation results demonstrate that the proposed approach outperforms two benchmark schemes in terms of the UE’s mean data rate and outage percentage.

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Section: The Proposed Localization Of Ground Ues and Their Associatio...mentioning

confidence: 99%

Q-learning-based UAV-mounted base station positioning in a disaster scenario for connectivity to the users located at unknown positions

Mandloi

Arya

2023

J Supercomput

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show abstract

“…First, we search each point p i in the point set P for its nearest point q i in the point set Q as the corresponding point. Then the corresponding set of P = {p 1 , p 2 , ...p n } is set to Q = {q 1 , q 2 , ...q n } to solve a European transformation R, t in order to satisfy (14).…”

Section: A Offloading Point Selectionmentioning

confidence: 99%

Partial Computing Offloading Assisted Cloud Point Registration in Multi-robot SLAM

Li¹,

Mi²,

Guo³

et al. 2019

Preprint

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Multi-robot visual simultaneous localization and mapping (SLAM) system is normally consisted of multiple mobile robots equipped with camera and/or other visual sensors. The networked robots work independently or cooperatively in an unknown scene in order to solve autonomous localization and mapping problem. One of the most critical issues in Multirobot visual SLAM is the intensive computation that is normally required yet overwhelming for inexpensive mobile robots with limited on-board resources. To address this problem, a novel task offloading strategy and dense point cloud map construction method is proposed in this paper. First, we develop a novel strategy to remotely offload computation-intensive tasks to cloud center, so that the tasks that could not originally be achieved locally on the resource-limited robot systems become possible. Second, a modified iterative closest point algorithm (ICP), named fitness score hierarchical ICP algorithm (FS-HICP), is developed to accelerate point cloud registration. The correctness, efficiency, and scalability of the proposed strategy are evaluated with both theoretical analysis and experimental simulations. The results show that the proposed method can effectively reduce the energy consumption while increase the computation capability and speed of the multi-robot visual SLAM system, especially in indoor environment.

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A new rock fracture reconstruction method under the constraints of microseismic location and focal mechanism

Zhao

Yang

Hou

et al. 2023

International Journal of Rock Mechanics and Mining Sciences

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An efficient approach for undelayed range-only SLAM based on Gaussian mixtures expectation

Cited by 13 publications

References 44 publications

Q-learning-based UAV-mounted base station positioning in a disaster scenario for connectivity to the users located at unknown positions

Q-learning-based UAV-mounted base station positioning in a disaster scenario for connectivity to the users located at unknown positions

Partial Computing Offloading Assisted Cloud Point Registration in Multi-robot SLAM

A new rock fracture reconstruction method under the constraints of microseismic location and focal mechanism

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