SwarmPath: Drone Swarm Navigation Through Cluttered Environments Leveraging Artificial Potential Field and Impedance Control

In the area of multi-drone systems, navigating through dynamic environments from start to goal while providing collision-free trajectory and efficient path planning is a significant challenge. To solve this problem, we propose a novel SwarmPath technology that involves the integration of artificial potential field (APF) approach with impedance controller. The proposed approach provides a solution based on collision-free leader-follower behaviour where drones are able to adapt themselves to the environment. Moreover, the leader is virtual while drones are physical followers, leveraging APF path planning approach to find the smallest possible path to the target. Simultaneously, the drones dynamically adjust impedance links, allowing themselves to create virtual links with obstacles to avoid them. As compared to conventional APF, the proposed SwarmPath system not only provides smooth collision avoidance but also enables agents to efficiently pass through narrow passages by reducing the total travel time by 30% while ensuring safety in terms of drone connectivity. Lastly, the results also illustrate that the discrepancies between the simulated and real environments exhibit an average absolute percentage error (APE) of 6% of drone trajectories. This underscores the reliability of our solution in real-world scenarios. Video: https://youtu.be/k8Nf_vPZf7U

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Publication Details

Published
2024-12-10
DOI
https://doi.org/10.1109/robio64047.2024.10907517
Citations
4
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
5.20

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article

SwarmPath: Drone Swarm Navigation Through Cluttered Environments Leveraging Artificial Potential Field and Impedance Control

Aleksey Fedoseev, Dzmitry Tsetserukou, Muhammad Nouman Zafar, Amber Batool et al.
4 citations
UAV Applications and Optimization
5.20
article

SwarmPath: Drone Swarm Navigation Through Cluttered Environments Leveraging Artificial Potential Field and Impedance Control

Aleksey Fedoseev, Dzmitry Tsetserukou, Muhammad Nouman Zafar, Amber Batool, Roohan Ahmed Khan
article en
4 citations

Abstract

In the area of multi-drone systems, navigating through dynamic environments from start to goal while providing collision-free trajectory and efficient path planning is a significant challenge. To solve this problem, we propose a novel SwarmPath technology that involves the integration of artificial potential field (APF) approach with impedance controller. The proposed approach provides a solution based on collision-free leader-follower behaviour where drones are able to adapt themselves to the environment. Moreover, the leader is virtual while drones are physical followers, leveraging APF path planning approach to find the smallest possible path to the target. Simultaneously, the drones dynamically adjust impedance links, allowing themselves to create virtual links with obstacles to avoid them. As compared to conventional APF, the proposed SwarmPath system not only provides smooth collision avoidance but also enables agents to efficiently pass through narrow passages by reducing the total travel time by 30% while ensuring safety in terms of drone connectivity. Lastly, the results also illustrate that the discrepancies between the simulated and real environments exhibit an average absolute percentage error (APE) of 6% of drone trajectories. This underscores the reliability of our solution in real-world scenarios. Video: https://youtu.be/k8Nf_vPZf7U

Skolkovo Institute of Science and Technology (RU)
Russian Science Foundation
Openalex Percentile: Top 5%
UAV Applications and Optimization
5.20
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SwarmPath: Drone Swarm Navigation Through Cluttered Environments Leveraging Artificial Potential Field and Impedance Control — Aleksey Fedoseev, Dzmitry Tsetserukou, et al. · (2024) | TGRS Research Map | TGRS