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SPARC: Spatial-Aware Path Planning via Attentive Robot Communication

arXiv – CS AI|Sayang Mu, Xiangyu Wu, Bo An|March 4, 2026 at 05:00 AM|1 views

🤖AI Summary

Researchers developed SPARC, a new AI system for multi-robot path planning that uses spatial-aware communication to improve coordination. The system achieved 75% success rate when scaling from 8 training robots to 128 test robots, outperforming existing methods by over 25 percentage points in high-density environments.

Key Takeaways

→SPARC introduces Relation enhanced Multi Head Attention (RMHA) that prioritizes communication based on spatial proximity between robots.
→The system demonstrates strong zero-shot generalization, scaling from 8 training robots to 128 test robots on 40x40 grids.
→SPARC achieved approximately 75% success rate at 30% obstacle density, significantly outperforming baseline methods.
→Distance-relation encoding was identified as the key factor driving success rate improvements in congested environments.
→The approach integrates with MAPPO for stable end-to-end training in decentralized multi-robot systems.

#multi-robot-systems #path-planning #attention-mechanism #ai-research #robotics #communication-optimization #machine-learning #spatial-awareness

Read Original →via arXiv – CS AI

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