Role of ant colony optimization in path planning of the robot: A review

Patle, B. K.; Wakchaure, Manas; Thorat, Tanmay; Gudadhe, Nitin

doi:10.1063/5.0183506

Cited by 2 publications

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Cooperative area searching method for UAV swarm based on wolf pack intelligence

2024

Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024)

View full text Add to dashboard Cite

For the cooperative searching problem of UAV swarm in unknown environment without prior information, an area covering search method inspired by swarm intelligence is proposed. First, the grid method is used to model the search environment discretely, and the UAV swarm cooperative covering search optimization model is established. Second, the creating and updating method for UAV search map is designed based on the scouting behavior of wolf pack. Third, considering the search reward and cost, the UAV cooperative search efficiency function and the search path decision method are constructed. The simulation results show that the proposed method can effectively improve the covering rate, and the search efficiency is significantly higher than that of random search method.

show abstract

Cooperative area searching method for UAV swarm based on wolf pack intelligence

2024

Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024)

View full text Add to dashboard Cite

show abstract

An improved RRT* drone three-dimensional path-planning algorithm based on point cloud maps

Zhao,

Wang,

Liu

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

Given the problems of slow convergence and blind sampling of the Rapidly-exploring Random Trees (RRT*) algorithm in 3D path-planning of UAVs, this paper proposes an improved bidirectional probabilistic target bias RRT* algorithm for 3D path-planning of UAVs based on point cloud maps. Initially, 3D point cloud maps and the dynamic step size necessary for the expansion of the RRT* algorithm are derived through the implementation of 3D map reconstruction and point cloud analysis techniques. Subsequently, a double sampling mechanism of random and target sampling is combined with the expansion strategy of the Bi-RRT* and RRT*-Connect algorithms to generate a bidirectional random tree, which improves the search speed and shortens the path. Furthermore, the influence of a gravitational mechanism, generated by the goal, is considered to direct the growth of the random tree toward the target. A collision avoidance strategy based on KD-tree is also introduced to enhance collision detection efficiency and mitigate collision risks. Additionally, cubic spline optimization is employed to achieve a smoother path. Finally, in order to illustrate the viability and efficacy of the proposed algorithm, a comparative analysis is performed between the enhanced algorithm and the RRT*, P-RRT*, and Bi-RRT* algorithms across two distinct environments.

show abstract

Role of ant colony optimization in path planning of the robot: A review

Cited by 2 publications

References 56 publications

Cooperative area searching method for UAV swarm based on wolf pack intelligence

Cooperative area searching method for UAV swarm based on wolf pack intelligence

An improved RRT* drone three-dimensional path-planning algorithm based on point cloud maps

Contact Info

Product

Resources

About