scholarly journals Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment with Multi-Criteria Decision Making using Full Consistency Method

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1241 ◽  
Author(s):  
Zagradjanin ◽  
Pamucar ◽  
Jovanovic
Keyword(s):  
Decision Making ◽  
Path Planning ◽  
Multi Criteria Decision Making ◽  
Robot Path Planning ◽  
Robot System ◽  
Global Cost ◽  
Consistency Method ◽  
Crowded Environment ◽  
Robot Path ◽  
Multi Robot

The progress in the research of various areas of robotics, artificial intelligence, and other similar scientific disciplines enabled the application of multi-robot systems in different complex environments and situations. It is necessary to elaborate the strategies regarding the path planning and paths coordination well in order to efficiently execute a global mission in common environment, prior to everything. This paper considers the multi-robot system based on the cloud technology with a high level of autonomy, which is intended for execution of tasks in a complex and crowded environment. Cloud approach shifts computation load from agents to the cloud and provides powerful processing capabilities to the multi-robot system. The proposed concept uses a multi-robot path planning algorithm that can operate in an environment that is unknown in advance. With the aim of improving the efficiency of path planning, the implementation of Multi-criteria decision making (MCDM) while using Full consistency method (FUCOM) is proposed. FUCOM guarantees the consistent determination of the weights of factors affecting the robots motion to be symmetric or asymmetric, with respect to the mission specificity that requires the management of multiple risks arising from different sources, optimizing the global cost map in that way.

Research and Implementation of Multi-robot Path Planning Based on Genetic Algorithm

2021 ◽  
Author(s):  
Mengqing Fan ◽  
Jiawang He ◽  
Susheng Ding ◽  
Yuanhao Ding ◽  
Meng Li ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Robot Path Planning ◽  
Robot Path ◽  
Multi Robot

scholarly journals Multi-robot path planning using an improved self-adaptive particle swarm optimization

2020 ◽  
Vol 17 (5) ◽  
pp. 172988142093615
Author(s):  
Biwei Tang ◽  
Kui Xiang ◽  
Muye Pang ◽  
Zhu Zhanxia
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Evolutionary Game ◽  
Particle Swarm ◽  
Computation Time ◽  
Robot Path Planning ◽  
Swarm Optimization ◽  
Robot Path ◽  
Self Adaptive ◽  
Multi Robot

Path planning is of great significance in motion planning and cooperative navigation of multiple robots. Nevertheless, because of its high complexity and nondeterministic polynomial time hard nature, efficiently tackling with the issue of multi-robot path planning remains greatly challenging. To this end, enhancing a coevolution mechanism and an improved particle swarm optimization (PSO) algorithm, this article presents a coevolution-based particle swarm optimization method to cope with the multi-robot path planning issue. Attempting to well adjust the global and local search abilities and address the stagnation issue of particle swarm optimization, the proposed particle swarm optimization enhances a widely used standard particle swarm optimization algorithm with the evolutionary game theory, in which a novel self-adaptive strategy is proposed to update the three main control parameters of particles. Since the convergence of particle swarm optimization significantly influences its optimization efficiency, the convergence of the proposed particle swarm optimization is analytically investigated and a parameter selection rule, sufficiently guaranteeing the convergence of this particle swarm optimization, is provided in this article. The performance of the proposed planning method is verified through different scenarios both in single-robot and in multi-robot path planning problems. The numerical simulation results reveal that, compared to its contenders, the proposed method is highly promising with respect to the path optimality. Also, the computation time of the proposed method is comparable with those of its peers.

Multi-robot path planning for smart access of distributed charging points in map

2020 ◽  
Author(s):  
Abhijeet Ravankar ◽  
Ankit A. Ravankar ◽  
Michiko Watanabe ◽  
Yohei Hoshino ◽  
Arpit Rawankar
Keyword(s):  
Path Planning ◽  
Robot Path Planning ◽  
Robot Path ◽  
Multi Robot
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