Obstacle Avoidance Algorithm for Multi-Robot Formation Based on Affine Transformation
Qiaolong Zhang, Yanhong Su, Youhang Zhou, Jing Sun, Zhe Zhou, Zilin Wan, Wenna Deng · Symmetry · 2025
Aiming at the problem that obstacle avoidance flexibility and formation integrity are difficult to coexist in multi-robot formation motion, a path-deformation mapping mechanism is proposed, which deeply integrates artificial potential field and affine transformation, and drives formation adaptive adjustment in real time through path information. By using the non-uniform scaling characteristics of the affine transformation, the limitation of traditional conformal transformation is broken through, and the unity of flexibility and integrity is realized. The effectiveness of the algorithm is verified by experiments, which provide a practical solution for cooperative obstacle avoidance of multi-robot systems in complex environments. In order to verify the performance of the algorithm, a numerical simulation is carried out, and an experimental platform composed of seven omnidirectional mobile robots is built for physical verification. The simulation and experimental results show that the formation can complete the obstacle avoidance task in the complex static obstacle environment, and the average formation tracking error is maintained below 0.05 m. Compared with the traditional local obstacle avoidance or formation switching method, this algorithm significantly improves the fluency of the obstacle avoidance process and the integrity of the formation while ensuring a success rate of 100% obstacle avoidance.