Role-Adaptive Collaborative Formation Planning for Team of Quadruped Robots in Cluttered Environments

• URL: http://arxiv.org/abs/2602.18260v1
• Date: Fri, 20 Feb 2026 14:44:16 GMT
• Title: Role-Adaptive Collaborative Formation Planning for Team of Quadruped Robots in Cluttered Environments
• Abstract summary: This paper presents a role-adaptive Leader-Follower-based formation planning and control framework for quadruped robots.<n>Unlike conventional methods with fixed leaders or rigid formation roles, the proposed approach integrates dynamic role assignment and partial goal planning.<n>Results demonstrate smooth coordination, switching adaptive role, and robust formation maintenance in complex, unstructured environments.
• Score: 15.679419362625845
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

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