A Robotic Path Planning by Using Crow Swarm Optimization Algorithm

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Mohammed Yousif 1,* Ahmad Salim 3 Wisam K. Jummar 2

1. Directorate of Regions and Governorates Affairs, Ministry of Youth & Sport, Iraq.

2. University of Anbar, Anbar, Iraq

3. Middle Technical University, Baghdad, Iraq

* Corresponding author.

DOI: https://doi.org/10.5815/ijmsc.2021.01.03

Received: 28 Dec. 2020 / Revised: 5 Jan. 2021 / Accepted: 18 Jan. 2021 / Published: 8 Feb. 2020

Index Terms

Robotic, Path planning, Meta-heuristic, Crow Swarm Optimization (CSO), Optimization.


One of the most common problem in the design of robotic technology is the path planning. The challenge is choosing the robotics’ path from source to destination with minimum cost. Meta-heuristic algorithms are popular tools used in a search process to get optimal solution. In this paper, we used Crow Swarm Optimization (CSO) to overcome the problem of choosing the optimal path without collision. The results of CSO compared with two meta-heuristic algorithms: PSO and ACO in addition to a hybrid method between these algorithms. The comparison process illustrates that the CSO better than PSO and ACO in path planning, but compared to hybrid method CSO was better whenever the smallest population. Consequently, the importance of research lies in finding a new method to use a new meta-humanistic algorithm to solve the problem of robotic path planning.

Cite This Paper

Mohammed Yousif, Ahmad Salim, Wisam K. Jummar," A Robotic Path Planning by Using Crow Swarm Optimization Algorithm ", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.7, No.1, pp. 20-25, 2021. DOI: 10.5815/ijmsc.2021.01.03


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