Multi-UAV Formation Cooperative Obstacle Avoidance and Adaptive Shape Deformation Control in Complex Environments Based on BI-APF-RRT and Affine Transformation
2026-06-29 • Robotics
Robotics
AI summaryⓘ
The authors address the challenge of keeping multiple drones flying in formation while avoiding obstacles. They improve path planning by combining a new method called BI-APF-RRT, which helps find smooth, safe routes without getting stuck, with a way to gently reshape the drone formation based on nearby obstacles. Their approach lets the drone group move safely and stay together, even in complex environments, by guiding the leader and having followers adapt accordingly.
multi-UAV formationobstacle avoidanceartificial potential field (APF)BI-APF-RRTaffine transformationcubic B-spline interpolationpath planningdistributed controllocal optima
Authors
Yiliang Wu, Weican Chen, Yendo Hu
Abstract
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.