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Efficient 3D Path Planning for Drone Swarm Using Improved Sine Cosine Algorithm

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Abstract

Path planning is one of the most important steps in the navigation and control of swarm of drones. It is primarily concerned with avoiding collision among drones and environmental obstacles while determining the most efficient flight path to the region of interest. Whenever there is a high density and complex mission, path planning becomes the most challenging and indispensable task. The problem of path planning is not only relevant to finding the optimum path from the start point to the destination point but also to provide a mechanism for preventing collisions on the path. Hence, an appropriate algorithm is needed to plan the optimal path for the swarm of drones. This paper proposes an efficient methodology for drone swarm path planning problems in 3D environments. An improved population-based meta-heuristic algorithm, Sine Cosine Algorithm (SCA), has been proposed to solve this problem. As part of the improvements, the population of SCA is initialized using a chaotic map, and a non-linearly decreasing step size is used to balance the local and global search. In addition, a convergence factor is employed to increase the convergence rate of the original SCA. The performance of the proposed improved SCA (iSCA) is tested over the drone swarm path planning problem, and the results are compared with those of the original SCA, and other state-of-the-art meta-heuristic algorithms. The experimental results show that the drone swarm 3D path planning problem can be efficiently handled with the proposed improved SCA.

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Acknowledgements

Author Jagdish Chand Bansal acknowledges the funding from Liverpool Hope University UK.

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Authors and Affiliations

  1. Department of Mathematics, South Asian University, New Delhi, 110068, New Delhi, India

    Probhat Pachung & Jagdish Chand Bansal

  2. Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Oxford Road, Manchester, M13 9PL, UK

    Kopal Pandya

  3. Department of Mathematics, Liverpool Hope University, Hope Park, Liverpool, L16 9JD, UK

    Atulya Nagar

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  1. Probhat Pachung
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  2. Kopal Pandya
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  3. Atulya Nagar
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  4. Jagdish Chand Bansal
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Contributions

PP: Conceptualization, methodology, writing original draft. KP, AN: Review, JCB: Supervision, review.

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Correspondence to Jagdish Chand Bansal.

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This article is part of the topical collection “Emerging Applications of Data Science for Real-World Problems” guest edited by Satyasai Jagannath Nanda, Rajendra Prasad Yadav and Mukesh Saraswat.

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Pachung, P., Pandya, K., Nagar, A. et al. Efficient 3D Path Planning for Drone Swarm Using Improved Sine Cosine Algorithm. SN COMPUT. SCI. 5, 286 (2024). https://doi.org/10.1007/s42979-024-02605-x

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