多无人机编队在复杂环境实现避障与自适应变形，兼顾安全与编队完整。
Multi-UAV Formation Cooperative Obstacle Avoidance and Adaptive Shape Deformation Control in Complex Environments Based on BI-APF-RRT and Affine Transformation
- 用改进的双向势场法结合RRT进行编队中心全局路径规划。
- 通过仿射变换实现编队在避障时动态调整形状，保持整体结构。
- 分布式控制让编队整体安全穿越障碍区，不解散且路径平滑。
针对多无人机编队在复杂障碍环境中避障灵活性与编队完整性难以兼顾，且传统人工势场法易陷入局部最优的问题，提出一种融合BI-APF-RRT与仿射变换的协同避障算法。首先，摒弃传统以质心为中心的路径规划方式，采用目标导向的双向人工势场RRT（BI-APF-RRT）算法，对编队质心进行全局无碰撞路径规划；通过引入改进的人工势场和三次B样条插值，确保全局路径的平滑性与快速收敛。其次，以生成的全局路径作为编队质心的引导轨迹，结合包含非均匀缩放与旋转的仿射变换矩阵，使编队在沿最优路径移动过程中能根据与障碍物距离自适应变形。最后，通过分布式控制律使跟随者跟踪领导者，确保整个编队安全穿越复杂障碍区域而不解体。
原文摘要 · Abstract (English)
Aiming at the problem that obstacle avoidance flexibility and formation integrity are difficult to coexist in multi-UAV formation motion in complex obstacle environments , and that the traditional artificial potential field (APF) method easily falls into local optima, a cooperative obstacle avoidance algorithm for multi-UAV formations integrating BI-APF-RRT and affine transformation is proposed. First, abandoning the traditional APF centroid path planning method , a goal-biased Bidirectional Artificial Potential Field method RRT (BI-APF-RRT) algorithm is adopted to conduct global collision-free path planning for the centroid of the leader formation. By introducing an improved artificial potential field and cubic B-spline interpolation, the smoothness and rapid convergence of the global path are ensured. Secondly, using the generated global path as the guiding trajectory for the formation's centroid , combined with an affine transformation matrix (including non-uniform scaling and rotation) , the formation can adaptively deform based on the distance to obstacles while moving along the optimal path. Finally, the followers track the leaders through a distributed control law , enabling the entire formation to safely cross complex obstacle areas without disassembling.
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