Contribution to the path planning of a multi-robot system: centralized architecture

2019 ◽  
Vol 13 (1) ◽  
pp. 147-158 ◽  
Author(s):  
Fethi Matoui ◽  
Boumedyen Boussaid ◽  
Brahim Metoui ◽  
Mohamed Naceur Abdelkrim
Keyword(s):  
Path Planning ◽  
Robot System ◽  
Multi Robot

scholarly journals Research Progress on Synergistic Technologies of Agricultural Multi-Robots

2021 ◽  
Vol 11 (4) ◽  
pp. 1448
Author(s):  
Wenju Mao ◽  
Zhijie Liu ◽  
Heng Liu ◽  
Fuzeng Yang ◽  
Meirong Wang
Keyword(s):  
Path Planning ◽  
Formation Control ◽  
Research Progress ◽  
Hybrid Architecture ◽  
Labor Costs ◽  
Robot System ◽  
System Architectures ◽  
Research Results ◽  
Robot Systems ◽  
Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

scholarly journals Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning

2021 ◽  
Vol 50 (2) ◽  
pp. 357-374
Author(s):  
Novak Zagradjanin ◽  
Aleksandar Rodic ◽  
Dragan Pamucar ◽  
Bojan Pavkovic
Keyword(s):  
Path Planning ◽  
High Efficiency ◽  
Fuzzy Inference ◽  
Learning Algorithm ◽  
Dynamic Environment ◽  
Cloud Services ◽  
Robot System ◽  
Inference System ◽  
Crowded Environment ◽  
Multi Robot

This paper considers an autonomous cloud-based multi-robot system designed to execute highly repetitive tasksin a dynamic environment such as a modern megastore. Cloud level is intended for performing the most demandingoperations in order to unload the robots that are users of cloud services in this architecture. For path planningon global level D* Lite algorithm is applied, bearing in mind its high efficiency in dynamic environments. In orderto introduce smart cost map for further improvement of path planning in complex and crowded environment, implementationof fuzzy inference system and learning algorithm is proposed. The results indicate the possibility ofapplying a similar concept in different real-world robotics applications, in order to reduce the total paths length,as well as to minimize the risk in path planning related to the human-robot interactions.

Distributed path planning of a multi-robot system based on the neighborhood artificial potential field approach

SIMULATION ◽  
2018 ◽  
Vol 95 (7) ◽  
pp. 637-657 ◽  
Author(s):  
Fethi Matoui ◽  
Boumedyen Boussaid ◽  
Mohamed Naceur Abdelkrim
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Robot System ◽  
Field Approach ◽  
Multi Robot

Path planning for the multi-robot system in intelligent warehouse

2017 ◽  
pp. 349-352
Author(s):  
DanLu Zhang ◽  
Bin Zheng ◽  
Shun Fu ◽  
Xiaoyong Sun
Keyword(s):  
Path Planning ◽  
Robot System ◽  
Multi Robot

scholarly journals A Path Planning for Coordinated Work by Multi-Robot System.

1993 ◽  
Vol 11 (2) ◽  
pp. 217-226 ◽  
Author(s):  
Motoji YAMAMOTO ◽  
Soumei KURODA ◽  
Akira MOHRI
Keyword(s):  
Path Planning ◽  
Robot System ◽  
Multi Robot

scholarly journals An Improved Real-Time Path Planning Method Based on Dragonfly Algorithm for Heterogeneous Multi-Robot System

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 140558-140568
Author(s):  
Jianjun Ni ◽  
Xiaotian Wang ◽  
Min Tang ◽  
Weidong Cao ◽  
Pengfei Shi ◽  
...  
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Planning Method ◽  
Robot System ◽  
Dragonfly Algorithm ◽  
Time Path ◽  
Multi Robot

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.

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