An Improved Sticky Bacteria Algorithm Fused with the Dynamic Window Approach for Multi-UAV Conflict Resolution

This article addresses real-time local conflict resolution for a self-planning UAV operating in a three-dimensional dynamic environment with surrounding UAVs. To this end, we develop an SBA–DWA hybrid planning framework in which an improved sticky bacteria algorithm (SBA) is embedded in the dynamic window approach (DWA) to enhance real-time velocity selection for the self-planning UAV. First, a chemotaxis operator with projection is developed to strictly constrain bacterial positions within the convex dynamic window. Furthermore, an anisotropic Gaussian adhesion potential field is proposed to adaptively guide the current population search using historical optimal velocity commands, achieving cross-step memory transfer. Then, a dynamic pruning mechanism is designed to ensure that historical memory does not lead UAVs into infeasible or hazardous regions. The proposed scheme guarantees that the single-step planning latency satisfies stringent real-time requirements. Comparative simulation results demonstrate that the proposed method reduces path length by approximately 30% and planning time by approximately 31% compared with the standard DWA, while achieving a larger minimum inter-vehicle clearance in dense dynamic scenarios.