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

2026-02-20

AI Summary

This work proposes a role-adaptive leader-follower formation framework for quadrupedal robot teams to address the challenges of obstacle avoidance and rigid coordination caused by fixed roles and inflexible formations in cluttered environments. The approach integrates dynamic role assignment, a hybrid global–local path planner based on Fast Marching Square (FM²), a look-ahead reference trajectory generator, and an adaptive obstacle avoidance layer. A virtual spring-damper model is introduced to enable velocity adaptation and temporary formation deformation. Experimental results demonstrate that the framework achieves smooth collaborative navigation, flexible role switching, and robust formation maintenance on both simulated and real quadrupedal robot platforms, significantly enhancing multi-robot coordination capabilities in unstructured environments.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Humans and AI: Teamwork, Team formation

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• Search and Retrieval-Augmented AI: Agentic search

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.

Problem

• quadruped robots
• formation planning
• cluttered environments
• role adaptation
• collision-free navigation

Innovation

• role-adaptive formation
• quadruped robot team
• dynamic role assignment
• obstacle avoidance layer
• Fast Marching Square