Assignment-Free Swarm Navigation via Adaptive Target-Field Planning and Mean-Shift Exploration

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Article Summary

Mean-shift exploration enables assignment-free swarm shape assembly, but obstacle-constrained navigation additionally requires coordinated adaptation of the desired morphology and its physical execution. This paper presents an environment-adaptive navigation framework that integrates target-field planning, execution regulation, and morphology-preserving mean-shift exploration. A feasibility-aware graph search plans the position, orientation, and morphology of an unlabeled target field without specifying robot-specific goals. An execution-regulated reference manager adjusts field progression and morphology switching using swarm entering, coverage, and lag metrics. A moving-frame controller separates prescribed rigid motion from local mean-shift redistribution and incorporates neighbor interactions and obstacle responses. Simulations and hardware experiments demonstrate that the proposed framework coordinates morphology transitions and collective motion for assignment-free swarm navigation through cluttered environments.

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