MemoryMesh: Shared Episodic Spatial Memory for Ground-Air Cooperative Search

Aayam Bansal, Ishaan Gangwani

Keywords: multi-robot exploration, search and rescue, spatial memory, UAV-UGV, communication-efficient coordination, frontier-based exploration

TL;DR: A shared episodic spatial memory with goal broadcasting enables low-bandwidth coordination for heterogeneous ground-air search.

Abstract: Multi-agent search-and-rescue requires tight coordination between heterogeneous robots, yet real-world communication constraints make sharing full sensory observations impractical. We introduce \method, a shared spatial memory for ground-air cooperative search that combines delta-encoded map sharing with a goal-broadcast coordination protocol. Each agent maintains a local spatial memory map of explored regions and broadcasts compact updates encoding newly observed cells together with its current navigation goal. A confidence-weighted merge resolves conflicts when agents observe the same region at different times. Coordination emerges from three mechanisms: goal exclusion zones that penalize frontiers near other agents' announced goals, persistent goal pursuit that reduces oscillation, and role-aware scoring that biases aerial agents toward open areas and ground agents toward wall-dense regions. In a 2D grid-world simulator with partial observability, occlusions, and heterogeneous sensing, we evaluate \method and its ablated variants against five baselines on both $80 \times 80$ and $150 \times 150$ environments. On the larger $150 \times 150$ maps with 40 targets, \method achieves the highest coverage (0.698) among all methods while using only 208 KB of communication, a $294\times$ reduction relative to full-map sharing at comparable scale. Goal broadcasting with exclusion (DeltaMapShareGoals) proves to be the strongest single coordination mechanism, finding all 20 targets on $80 \times 80$ maps with only 100 KB bandwidth and near-zero overlap. Ablations over goal exclusion radius, replanning interval, and component contributions isolate the effect of each mechanism. Robustness experiments confirm graceful degradation under sensor noise (up to 20%), UAV partial occlusion (up to 70%), and packet loss (up to 40%, with zero target degradation). Scaling tests from 2 to 4 agents and from $60 \times 60$ to $120 \times 120$ maps demonstrate consistent behavior.

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Submission Number: 6