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...

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Bibliographic Details
Published inIEEE International Conference on Robotics and Biomimetics (Online) pp. 402 - 407
Main Authors Khan, Roohan Ahmed, Zafar, Malaika, Batool, Amber, Fedoseev, Aleksey, Tsetserukou, Dzmitry
Format Conference Proceeding
LanguageEnglish
Published IEEE 10.12.2024
Subjects
Adaptive Systems
Artificial Potential Field
Collision avoidance
Control systems
Cooperative Systems
Drones
Formation Control
Impedance
Impedance Control
Navigation
Path Planning
Reliability
Robots
Safety
Swarm
Trajectory
Virtual links
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ISSN2994-3574
DOI10.1109/ROBIO64047.2024.10907517

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Summary: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
ISSN:2994-3574
DOI:10.1109/ROBIO64047.2024.10907517