Reason-to-Transmit: Deliberative Adaptive Communication for Cooperative Perception

2026-03-24 · Source: cs.MA updates on arXiv.org · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems · Depth: Advanced, extended

Summary

Reason-to-Transmit (R2T) is a novel framework designed to enhance cooperative perception in autonomous agents by introducing a deliberative communication policy. Unlike existing reactive methods that decide what to transmit based on local confidence or learned gating, R2T employs a lightweight transformer-based reasoning module (0.26M parameters) to consider local scene context, estimated neighbor information gaps, and the current bandwidth budget before making per-region transmit decisions. Evaluated in a synthetic multi-agent bird's-eye-view (BEV) perception environment with four agents and configurable occlusion, R2T was compared against nine baselines, including Where2Comm and IC3Net. The framework demonstrates a dramatic ~58% Average Precision (AP) improvement over no communication, confirming the effectiveness of its gated fusion module. R2T particularly excels under high occlusion, achieving 0.205 AP, matching the oracle upper bound and outperforming Where2Comm (0.203 AP) and IC3Net (0.202 AP) by reasoning about what receivers cannot see.

Key takeaway

For AI Scientists and Computer Vision Engineers developing cooperative perception systems, prioritizing the design of robust gated fusion modules is paramount, as it yields the largest performance gains. While any communication improves performance by ~58% AP, integrating deliberative reasoning like R2T's transformer-based approach will provide critical incremental advantages in highly occluded or information-asymmetric environments, ensuring more efficient bandwidth use by transmitting only what the receiver truly needs.

Key insights

Deliberative communication, considering receiver information gaps, significantly boosts cooperative perception, especially under high occlusion.

Principles

• Fusion module design is critical for cooperative perception gains.
• Deliberative reasoning improves communication efficiency.
• Communication always helps with proper fusion.

Method

R2T uses a transformer to reason over local features, neighbor information gaps, and bandwidth, generating per-region transmit probabilities. Regions are ranked by $p_{i}^{(k)}\cdot s_{i}^{(k)}$ and top regions are selected.

In practice

• Prioritize fusion module design in cooperative perception.
• Use neighbor state estimates for communication decisions.
• Employ a budget token to adapt transmission selectivity.

Topics

• Cooperative Perception
• V2X Communication
• Multi-Agent Systems
• Transformer Models
• Deliberative Reasoning

Best for: Computer Vision Engineer, AI Scientist, Research Scientist, AI Researcher, Robotics Engineer, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.MA updates on arXiv.org.