This paper presents a role-adaptive Leader-Follower-based formation planning and control framework for teams of quadruped robots operating in cluttered environments. Unlike conventional methods with fixed leaders or rigid formation roles, the proposed approach integrates dynamic role assignment and partial goal planning, enabling flexible, collision-free navigation in complex scenarios. Formation stability and inter-robot safety are ensured through a virtual spring-damper system coupled with a novel obstacle avoidance layer that adaptively adjusts each agent's velocity. A dynamic look-ahead reference generator further enhances flexibility, allowing temporary formation deformation to maneuver around obstacles while maintaining goal-directed motion. The Fast Marching Square (FM2) algorithm provides the global path for the leader and local paths for the followers as the planning backbone. The framework is validated through extensive simulations and real-world experiments with teams of quadruped robots. Results demonstrate smooth coordination, adaptive role switching, and robust formation maintenance in complex, unstructured environments. A video featuring the simulation and physical experiments along with their associated visualizations can be found at https://youtu.be/scq37Tua9W4.

翻译：本文提出了一种基于角色自适应的领导者-跟随者编队规划与控制框架，适用于在杂乱环境中运行的四足机器人团队。与采用固定领导者或刚性编队角色的传统方法不同，所提方法集成了动态角色分配和部分目标规划，从而能够在复杂场景中实现灵活、无碰撞的导航。通过虚拟弹簧阻尼系统与一个新颖的避障层相结合，确保了编队稳定性和机器人间的安全性，该避障层自适应地调整每个智能体的速度。动态前瞻参考生成器进一步增强了灵活性，允许编队临时变形以绕过障碍物，同时保持朝向目标的运动。Fast Marching Square (FM2) 算法作为规划主干，为领导者提供全局路径，为跟随者提供局部路径。该框架通过广泛的仿真和四足机器人团队的实物实验得到了验证。结果表明，在复杂、非结构化的环境中，系统实现了平滑协调、自适应角色切换和鲁棒的编队保持。包含仿真和物理实验及其相关可视化的视频可在 https://youtu.be/scq37Tua9W4 找到。