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This paper introduces SALFDG, a Synergistic Alpha-Led Force-Driven Gradient algorithm designed to enhance UAV swarm path-planning with a focus on urgency and reliability in unknown environments. Building on our previous research, we integrate the strengths of reinforcement learning-based, bio-inspired, and physics-based algorithms to address previously identified limitations. We conduct extensive simulations to validate the performance of SALFDG, demonstrating its effectiveness in diverse environments.

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Synergistic Alpha-Led Force-Driven Gradient to Address Urgency and Reliability in Swarm Intelligence Path-Planning

  • 会议论文

  • 发表日期：

    2026年

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  • Sean Tseng,
  • Tabatha Viso,
  • Max Weissman,
  • Chun-Kit Ngan

摘要

This paper introduces SALFDG, a Synergistic Alpha-Led Force-Driven Gradient algorithm designed to enhance UAV swarm path-planning with a focus on urgency and reliability in unknown environments. Building on our previous research, we integrate the strengths of reinforcement learning-based, bio-inspired, and physics-based algorithms to address previously identified limitations. We conduct extensive simulations to validate the performance of SALFDG, demonstrating its effectiveness in diverse environments.