Author:
Song Baoye,Tang Shumin,Li Yao
Abstract
<abstract><p>This article is concerned with the path planning of mobile robots in dynamic environments. A new path planning strategy is proposed by integrating the improved ant colony optimization (ACO) and dynamic window approach (DWA) algorithms. An improved ACO is developed to produce a globally optimal path for mobile robots in static environments. Through improvements in the initialization of pheromones, heuristic function, and updating of pheromones, the improved ACO can lead to a shorter path with fewer turning points in fewer iterations. Based on the globally optimal path, a modified DWA is presented for the path planning of mobile robots in dynamic environments. By deleting the redundant nodes, optimizing the initial orientation, and improving the evaluation function, the modified DWA can result in a more efficient path for mobile robots to avoid moving obstacles. Some simulations are conducted in different environments, which confirm the effectiveness and superiority of the proposed path planning algorithms.</p></abstract>
Publisher
American Institute of Mathematical Sciences (AIMS)
Reference44 articles.
1. S. Zhu, W. Zhu, X. Zhang, T. Cao, Path planning of lunar robot based on dynamic adaptive ant colony algorithm and obstacle avoidance, Int. J. Adv. Rob. Syst., 17 (2020). http://doi.org/10.1177/1729881419898979
2. E. Fernandes, P. Costa, J. Lima, G. Veiga, Towards an orientation enhanced astar algorithm for robotic navigation, in 2015 IEEE International Conference on Industrial Technology (ICIT), (2015), 3320–3325. https://doi.org/10.1109/ICIT.2015.7125590
3. L. Liu, X. Wang, X. Yang, H. Liu, J. Li, P. Wang, Path planning techniques for mobile robots: Review and prospect, Expert Syst. Appl., 227 (2023), 120254. https://doi.org/10.1016/j.eswa.2023.120254
4. G. Che, L. Liu, Z. Yu, An improved ant colony optimization algorithm based on particle swarm optimization algorithm for path planning of autonomous underwater vehicle, J. Ambient Intell. Hum. Comput., 11 (2020), 3349–3354. https://doi.org/10.1007/s12652-019-01531-8
5. A. Yazici, G. Kirlik, O. Parlaktuna, A. Sipahioglu, A dynamic path planning approach for multirobot sensor-based coverage considering energy constraints, IEEE Trans. Cybern., 44 (2014), 305–314. https://doi.org/10.1109/TCYB.2013.2253605
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