Article

DSGN: A Dual-Stream Gated Network for Scalable Multi-Robot Surveillance and Containment

The authors propose the Dual-Stream Gated Network (DSGN), which separates surveillance and containment into independent representation streams and coordinates them through a context-aware gating mechanism to alleviate task-switching difficulties in large-scale robot networks. The method also introduces a probabilistic prior to regularize the gating process, reducing ambiguous intermediate decisions. Under constant-density cross-scale settings, DSGN maintains task effectiveness and scalability; ablation and staged experiments show that dynamic gating and the probabilistic prior support task arbitration and mode switching. The paper has been accepted to RA-L October 2026, and the code is publicly available.

Part of the event: DSGN Dual-Stream Gated Network for Multi-Robot Surveillance and Encirclement

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