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VIRGA: Virtual-Agent-Intermediated Riemannian Geometry for Active-Sensing Air-Ground Coordination

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Air-ground autonomy becomes harder when the unmanned aerial vehicle (UAV) must remain observable by a gimbal light detection and ranging (LiDAR) mounted on the unmanned ground vehicle (UGV). The platforms must avoid dynamic obstacles while coordinating heterogeneous motion, limited sensing, and changing task initiative within one closed loop. This paper presents VIRGA, a neural geometric coordination framework that turns dual-LiDAR observations into bounded source-specific Riemannian fields and couples them through a virtual agent with reciprocal elastic feedback. Platform-aware execution maps

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