An Evolutionary Learning Approach for Robot Path Planning with Fuzzy Obstacle Detection and Avoidance in a Multi-agent Environment

2012 ◽  
Author(s):  
Taua M. Cabreira ◽  
Gracaliz P. Dimuro ◽  
Marilton S. de de Aguiar
Keyword(s):  
Path Planning ◽  
Obstacle Detection ◽  
Learning Approach ◽  
Evolutionary Learning ◽  
Robot Path Planning ◽  
Multi Agent ◽  
Robot Path

scholarly journals Applications and Challenges of Deep Reinforcement Learning in Multi-robot Path Planning

2021 ◽  
Vol 5 (6) ◽  
pp. 25-29
Author(s):  
Tianyun Qiu ◽  
Yaxuan Cheng
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Research Area ◽  
Training Methods ◽  
Multi Agent Systems ◽  
Robot Path Planning ◽  
Practical Applications ◽  
Multi Agent ◽  
Robot Path ◽  
Multi Robot

With the rapid advancement of deep reinforcement learning (DRL) in multi-agent systems, a variety of practical application challenges and solutions in the direction of multi-agent deep reinforcement learning (MADRL) are surfacing. Path planning in a collision-free environment is essential for many robots to do tasks quickly and efficiently, and path planning for multiple robots using deep reinforcement learning is a new research area in the field of robotics and artificial intelligence. In this paper, we sort out the training methods for multi-robot path planning, as well as summarize the practical applications in the field of DRL-based multi-robot path planning based on the methods; finally, we suggest possible research directions for researchers.

A Multilevel Learning Approach to Mobile Robot Path Planning

1995 ◽  
pp. 215-228 ◽  
Author(s):  
F. Wallner ◽  
M. Kaiser ◽  
H. Friedrich ◽  
R. Dillmann
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Learning Approach ◽  
Robot Path Planning ◽  
Robot Path

Numerical Potential Field Techniques for Robot Path Planning.

1989 ◽  
Author(s):  
Jerome Barraquand ◽  
Bruno Langlois ◽  
Jean-Claude Latombe
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Robot Path Planning ◽  
Field Techniques ◽  
Robot Path
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