A Revisiting Method Using a Covariance Traveling Salesman Problem Algorithm for Landmark-Based Simultaneous Localization and Mapping

Ryu, Hyejeong

doi:10.3390/s19224910

Cited by 7 publications

(5 citation statements)

References 38 publications

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“…There are some extended traveling salesman problems applications in [18][19][20][21][22]. An effective revisiting algorithm for simultaneous localization and mapping using landmarks is presented by Hyejeong Ryu [23] to choose positions to revisit by taking into account both landmark visibility and sensor measurement uncertainty in TSP. Schiffer et al [24] present integrated planning for electric commercial vehicle fleets: A case study for retail mid-haul logistics networks.…”

Section: Methodsmentioning

confidence: 99%

Assessing the Sustainability of the Prepandemic Impact on Fuzzy Traveling Sellers Problem with a New Fermatean Fuzzy Scoring Function

Baranidharan¹,

Meidutė‐Kavaliauskienė

Mahapatra³

et al. 2022

Sustainability

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This article focused on transportation sustainability during the COVID-19 pandemic situation under the Fermatean fuzzy environment. In both developed and developing nations, sustainability has risen to the top of the priority list for transportation policies and planning. We introduce a simplified presentation of the Fermatean fuzzy traveling seller problem solved by using a new computation approach. Several approaches for solving the traveling seller problem using fuzzy parameters have been described in the literature. Even so, all the current strategies use general fuzzy numbers as the parameters for the traveling salesman problems, but his study, focused on the new Fermatean fuzzy number, is more effective for representing real-life incidents. The Fermatean fuzzy scoring functions and numerical conditions in distinct models in the Fermatean fuzzy environment were described to construct the algorithm. New solution methodology developed through scoring functions to find the best solution to fulfill our goal of sustainable transportation for traveling sellers problem. Sustainable cost and the optimal path are obtained by this study.

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Section: Methodsmentioning

confidence: 99%

Assessing the Sustainability of the Prepandemic Impact on Fuzzy Traveling Sellers Problem with a New Fermatean Fuzzy Scoring Function

Baranidharan¹,

Meidutė‐Kavaliauskienė

Mahapatra³

et al. 2022

Sustainability

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“…Також не враховано важливість зон території. У [7] представлено алгоритм повторного перегляду для одночасної локалізації та відображення на основі орієнтирів (simultaneous localization and mapping -SLAM). Оптимальний шлях серед обраних позицій отримується застосуванням алгоритму задачі комівояжера.…”

Section: аналіз сучасних досліджень та постановка проблемиunclassified

“…Мінімальне значення енерговитрат досягається при побудові траєкторії, що проходить кожну точку лише один раз та має мінімальну довжину. Таким чином, задачу (6), (7) представимо у вигляді задачі комівояжера.…”

Section: рисunclassified

Optimization of the Trajectory of Sensors Motion Taking Into Account the Importance of the Areas of the Monitoring Area Segments and the Probability of Detection of Objects

Petrivskyi¹,

Petrivskyi²,

Шевченко³

et al. 2022

JAIS

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Due to the widespread use of sensors in data collection and processing, one of the key criteria is the amount of information accumulated and energy efficiency. While monitoring the territory, the movement of research objects is common. As a result there is a change in the probability of their detection in the segment of the territory. Also, segments may be of varying importance. Taking these factors into account will significantly increase the amount of information accumulated. The article presents a method of constructing the optimal trajectory of sensors motion taking into account the importance of territory segments and the probability of detection of objects. The method is based on the representation of distribution of the probability of detection of objects and the importance of territory segments in the form of layers and their integration into a layer of the probable value of detected objects. Seven classes of the probable value of detected objects with corresponding numerical and graphical equivalents are considered. As optimal trajectory of sensors motion the trajectory which provides minimum energy expenditure is meant. Energy efficiency is achieved by constructing a trajectory of minimum length as a solution to the salesman’s problem. The set of points at which the trajectory is built is formed on the basis of the layer of the probable value of the detected objects after the procedure of replacing the nodes. A separate node replacement class, or superposition of node replacement classes, is proposed for each class of probable value of detected objects. Replacement of five, three and two nodes is described. A genetic algorithm with modification of crossing and selection rules was used to find a solution to this problem. A set of trajectories is constructed using the proposed algorithm. The analysis of the obtained results confirmed the efficiency of the developed method and allowed to increase the energy efficiency when covering a given area by 76 %.

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“…The robot goes back to the parent node after exploring all child nodes during the "induced" loop-closing, and the nearest child or sibling node was selected as the next target according to the previous method. In this paper, we treat finding an efficient loop-closing path, an efficient exploration order, among the parent and the child nodes as solving a TSP [33,34]. Using the shortest traveling distance, dist i,j in Edge new , is the cost matrix of the TSP algorithm, we decide the exploration priority for the current and new nodes.…”

Section: Frontier Segmentationmentioning

confidence: 99%

Graph Search-Based Exploration Method Using a Frontier-Graph Structure for Mobile Robots

Ryu

2020

Sensors

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This paper describes a graph search-based exploration method. Segmented frontier nodes and their relative transformations constitute a frontier-graph structure. Frontier detection and segmentation are performed using local grid maps of adjacent nodes. The proposed frontier-graph structure can systematically manage local information according to the exploration state and overcome the problem caused by updating a single global grid map. The robot selects the next target using breadth-first search (BFS) exploration of the frontier-graph. The BFS exploration is improved to generate an efficient loop-closing sequence between adjacent nodes. We verify that our BFS-based exploration method can gradually extend the frontier-graph structure and efficiently map the entire environment, regardless of the starting position.

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A Revisiting Method Using a Covariance Traveling Salesman Problem Algorithm for Landmark-Based Simultaneous Localization and Mapping

Cited by 7 publications

References 38 publications

Assessing the Sustainability of the Prepandemic Impact on Fuzzy Traveling Sellers Problem with a New Fermatean Fuzzy Scoring Function

Assessing the Sustainability of the Prepandemic Impact on Fuzzy Traveling Sellers Problem with a New Fermatean Fuzzy Scoring Function

Optimization of the Trajectory of Sensors Motion Taking Into Account the Importance of the Areas of the Monitoring Area Segments and the Probability of Detection of Objects

Graph Search-Based Exploration Method Using a Frontier-Graph Structure for Mobile Robots

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