TY - JOUR
T1 - A*-Based Co-Evolutionary Approach for Multi-Robot Path Planning with Collision Avoidance
AU - Kiadi, Morteza
AU - García, Enol
AU - Villar, José R.
AU - Tan, Qing
N1 - Publisher Copyright:
© 2022 Taylor & Francis Group, LLC.
PY - 2023
Y1 - 2023
N2 - In this research, a coevolutionary collision free multi-robot path planning that makes use of A* is proposed. To find collision-free paths for all robots, we generate a route for each of robot using A* path finding but introducing restrictions for each collision found. Afterward, a co-evolutionary optimization process is implemented for introducing changes in the initial paths to find a combination of routes that is collision-free. The approach has been tested in mazes with increasing the number of robots, showing a robust performance although at high time expenses. Nevertheless, several enhancements are proposed to tackle this issue.
AB - In this research, a coevolutionary collision free multi-robot path planning that makes use of A* is proposed. To find collision-free paths for all robots, we generate a route for each of robot using A* path finding but introducing restrictions for each collision found. Afterward, a co-evolutionary optimization process is implemented for introducing changes in the initial paths to find a combination of routes that is collision-free. The approach has been tested in mazes with increasing the number of robots, showing a robust performance although at high time expenses. Nevertheless, several enhancements are proposed to tackle this issue.
KW - A algorithm
KW - co-evolutionary algorithms
KW - evolutionary algorithms
KW - multi-robot path planning
UR - http://www.scopus.com/inward/record.url?scp=85124218574&partnerID=8YFLogxK
U2 - 10.1080/01969722.2022.2030009
DO - 10.1080/01969722.2022.2030009
M3 - Journal Article
AN - SCOPUS:85124218574
SN - 0196-9722
VL - 54
SP - 339
EP - 354
JO - Cybernetics and Systems
JF - Cybernetics and Systems
IS - 3
ER -