scholarly journals Path Selection for the Inspection Robot by m-Generalized q-Neutrosophic PROMETHEE Approach

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 223
Author(s):  
Romualdas Bausys ◽  
Edmundas Kazimieras Zavadskas ◽  
Rokas Semenas
Keyword(s):  
Path Planning ◽  
Input Data ◽  
Target Position ◽  
Path Selection ◽  
Multi Criteria Decision Making ◽  
Optimal Route ◽  
Inspection Robot ◽  
Selection For ◽  
Assessment Requirements

Path planning can be considered the most vital task of the autonomous robot. In this task, selecting an optimal route from the starting to the target position becomes an important problem that must be addressed when multiple competing optimization priorities are considered. Thus, a novel route assessment strategy based on a multi-criteria decision-making approach is proposed. The m-generalized q-neutrosophic PROMETHEE (PROMETHEE-mGqNS) method is applied to aggregate the competing route assessment requirements and choose an optimal route. A case study is investigated to explain the proposed strategy for path planning in a typical environment and indicates the method stability when incomplete input data characteristics are present.

scholarly journals A New Online Random Particles Optimization Algorithm for Mobile Robot Path Planning in Dynamic Environments

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Behrang Mohajer ◽  
Kourosh Kiani ◽  
Ehsan Samiei ◽  
Mostafa Sharifi
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimization Algorithm ◽  
Potential Field ◽  
Optimal Path ◽  
Target Position ◽  
Path Selection ◽  
Artificial Potential Field ◽  
Planning Problem ◽  
Robot Path

A new algorithm named random particle optimization algorithm (RPOA) for local path planning problem of mobile robots in dynamic and unknown environments is proposed. The new algorithm inspired from bacterial foraging technique is based on particles which are randomly distributed around a robot. These particles search the optimal path toward the target position while avoiding the moving obstacles by getting help from the robot’s sensors. The criterion of optimal path selection relies on the particles distance to target and Gaussian cost function assign to detected obstacles. Then, a high level decision making strategy will decide to select best mobile robot path among the proceeded particles, and finally a low level decision control provides a control signal for control of considered holonomic mobile robot. This process is implemented without requirement to tuning algorithm or complex calculation, and furthermore, it is independent from gradient base methods such as heuristic (artificial potential field) methods. Therefore, in this paper, the problem of local mobile path planning is free from getting stuck in local minima and is easy computed. To evaluate the proposed algorithm, some simulations in three various scenarios are performed and results are compared by the artificial potential field.

scholarly journals Target position and avoidance margin effects on path planning in obstacle avoidance

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohammad R. Saeedpour-Parizi ◽  
Shirin E. Hassan ◽  
Ariful Azad ◽  
Kelly J. Baute ◽  
Tayebeh Baniasadi ◽  
...  
Keyword(s):  
Path Planning ◽  
Task Performance ◽  
Obstacle Avoidance ◽  
Visual Information ◽  
Target Location ◽  
Target Position ◽  
Path Selection ◽  
Deviation Angle ◽  
The Gaze ◽  
The Way

AbstractThis study examined how people choose their path to a target, and the visual information they use for path planning. Participants avoided stepping outside an avoidance margin between a stationary obstacle and the edge of a walkway as they walked to a bookcase and picked up a target from different locations on a shelf. We provided an integrated explanation for path selection by combining avoidance margin, deviation angle, and distance to the obstacle. We found that the combination of right and left avoidance margins accounted for 26%, deviation angle accounted for 39%, and distance to the obstacle accounted for 35% of the variability in decisions about the direction taken to circumvent an obstacle on the way to a target. Gaze analysis findings showed that participants directed their gaze to minimize the uncertainty involved in successful task performance and that gaze sequence changed with obstacle location. In some cases, participants chose to circumvent the obstacle on a side for which the gaze time was shorter, and the path was longer than for the opposite side. Our results of a path selection judgment test showed that the threshold for participants abandoning their preferred side for circumventing the obstacle was a target location of 15 cm to the left of the bookcase shelf center.

scholarly journals Target Position and Safety Margin Effects on Path Planning in Obstacle Avoidance

2021 ◽  
Author(s):  
Mohammad R. Saeedpour-parizi ◽  
Shirin E. Hassan ◽  
Ariful Azad ◽  
Kelly J. Baute ◽  
Tayebeh Baniasadi ◽  
...  
Keyword(s):  
Path Planning ◽  
Visual Information ◽  
Safety Margin ◽  
Target Position ◽  
Path Selection ◽  
Deviation Angle ◽  
Straight Line ◽  
Safety Margins ◽  
Planning Decision ◽  
The Right

Abstract This study examined how people choose their path to a target, and the visual information they use for path planning. Participants avoided making contact with an obstacle as they walked to a bookcase and picked up a cup from different locations on a shelf. Participants chose a path with a smaller deviation angle from a straight line to the target and chose a side of the obstacle which was closer to them. Unlike previous studies which have not included a safety margin in their analyses, we found that the right and left safety margins combined to account for 26% of the variability in path planning decision making. In some cases, participants chose a longer path around the obstacle even when the available safety margin which would have resulted in a straight line to the target was large enough to allow passage. Gaze analysis findings showed that participants directed their gaze to minimize the uncertainty involved in successful task performance and that gaze sequence changed with obstacle location. Early in their walk to the target, the greatest allocation of gaze was on the safety margin and target, later in their walk, gaze shifted to the safety margin when it was small, and then gaze shifted primarily to the target after the participant passed the obstacle. Our results of a path selection judgment test showed that the threshold for participants abandoning their preferred side for circumventing the obstacle was 15 cm to the left of the bookcase shelf center.

Multi-Criteria Decision Making for Vulnerability Mapping of Flood Hazard: A Case Study of Pune City

2019 ◽  
Vol 2 (1) ◽  
pp. 41-52
Author(s):  
Nitin Mundhe
Keyword(s):  
Decision Making ◽  
Flood Hazard ◽  
Geographical Information ◽  
Multi Criteria Decision Making ◽  
Flood Hazards ◽  
Very High Frequency ◽  
Flood Vulnerability ◽  
Natural Risk ◽  
The Town

Floods are natural risk with a very high frequency, which causes to environmental, social, economic and human losses. The floods in the town happen mainly due to human made activities about the blockage of natural drainage, haphazard construction of roads, building, and high rainfall intensity. Detailed maps showing flood vulnerability areas are helpful in management of flood hazards. Therefore, present research focused on identifying flood vulnerability zones in the Pune City using multi-criteria decision-making approach in Geographical Information System (GIS) and inputs from remotely sensed imageries. Other input data considered for preparing base maps are census details, City maps, and fieldworks. The Pune City classified in to four flood vulnerability classes essential for flood risk management. About 5 per cent area shows high vulnerability for floods in localities namely Wakdewadi, some part of the Shivajinagar, Sangamwadi, Aundh, and Baner with high risk.

scholarly journals Coupling Fuzzy Multi-Criteria Decision-Making and Clustering Algorithm for MSW Landfill Site Selection (Case Study: Lanzhou, China)

2021 ◽  
Vol 10 (6) ◽  
pp. 403
Author(s):  
Jiamin Liu ◽  
Yueshi Li ◽  
Bin Xiao ◽  
Jizong Jiao
Keyword(s):  
Decision Making ◽  
Clustering Algorithm ◽  
Fuzzy Membership Function ◽  
Multi Criteria Decision Making ◽  
Landfill Site Selection ◽  
Spatial Distribution Characteristics ◽  
Criteria Weights ◽  
Spatial Decision Making ◽  
Complex Decision

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.

A Case Study on Experiment Site Selection for PV Energy Generation Forecast

2020 ◽  
Author(s):  
Huang Yu Hsiang ◽  
Tseng Sheng Yuan ◽  
Ping Wang ◽  
Lin Wen Hui ◽  
Lin Hsiao Chung
Keyword(s):  
Site Selection ◽  
Energy Generation ◽  
Selection For

scholarly journals Path Planning for Autonomous Ships: A Hybrid Approach Based on Improved APF and Modified VO Methods

2021 ◽  
Vol 9 (7) ◽  
pp. 761
Author(s):  
Liang Zhang ◽  
Junmin Mou ◽  
Pengfei Chen ◽  
Mengxia Li
Keyword(s):  
Path Planning ◽  
Local Minimum ◽  
Hybrid Approach ◽  
Artificial Potential Field ◽  
Whole Process ◽  
International Regulations ◽  
Local Path ◽  
Velocity Obstacle ◽  
Global And Local

In this research, a hybrid approach for path planning of autonomous ships that generates both global and local paths, respectively, is proposed. The global path is obtained via an improved artificial potential field (APF) method, which makes up for the shortcoming that the typical APF method easily falls into a local minimum. A modified velocity obstacle (VO) method that incorporates the closest point of approach (CPA) model and the International Regulations for Preventing Collisions at Sea (COLREGS), based on the typical VO method, can be used to get the local path. The contribution of this research is two-fold: (1) improvement of the typical APF and VO methods, making up for previous shortcomings, and integrated COLREGS rules and good seamanship, making the paths obtained more in line with navigation practice; (2) the research included global and local path planning, considering both the safety and maneuverability of the ship in the process of avoiding collision, and studied the whole process of avoiding collision in a relatively entirely way. A case study was then conducted to test the proposed approach in different situations. The results indicate that the proposed approach can find both global and local paths to avoid the target ship.

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