发表机构
Oregon State University; MIT（俄勒冈州立大学; 麻省理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出MMOCIC框架，将协同进化与合规性行为解耦，在多机器人海洋任务中平衡团队进展与规范遵守，硬件部署8个、仿真12个机器人时均实现高性能且无碰撞。
AI 中文摘要
协作机器人非常适合需要协同的海上任务，例如未知礁体结构勘探、海底基础设施检查或搜救行动。这类任务通常仅提供稀疏的反馈信号来衡量进展，且需遵守安全和监管规范，因此任务转化为多目标优化问题。协同进化算法可处理这些稀疏反馈信号以生成协作行为，部分情况下还能将行为扩展至多目标。然而，动态结合高层团队目标与低层合规性考量，以平衡规范遵守与团队性能的问题仍未解决。本文提出一种多目标框架，将协同进化行为与合规性行为融合，以在最大化团队进展与最小化违规行为间取得平衡。核心思路是将学习与合规性解耦，因为操作规范是既定的而非需要发现的。我们在协作游泳者救援任务中验证了该框架：硬件部署时最多8个机器人，仿真中最多12个机器人，均实现了高团队性能且避免碰撞。本文的核心贡献是海洋多目标合规性集成协同进化算法（MMOCIC），该框架将团队范围优化与既定规范融合，适用于基于学习的协作的实际部署。
英文摘要
Collaborative robots are well-suited to maritime missions that benefit from coordination, such as the exploration of unknown reef structures, inspection of subsea infrastructure, or search-and-rescue operations. These missions typically provide sparse feedback signals for measuring progress and require adherence to safety and regulatory norms, turning a mission into a multi-objective optimization problem. Coevolutionary algorithms can process these sparse feedback signals to generate coordinated behaviors, and in some cases extend behaviors to multiple objectives. However, incorporating high-level team objectives with low-level compliance considerations on the fly to balance norm adherence with team performance remains elusive. This paper introduces a multi-objective framework that blends coevolved behaviors with compliance behaviors to achieve a balance between maximizing team progress and minimizing norm violations. The key insight is to decouple learning from compliance since operational norms are prescribed rather than discovered. We demonstrate that our framework achieves high team performance while avoiding collisions on a collaborative swimmer rescue mission with up to 8 vehicles in a hardware deployment, and 12 vehicles in simulation. The key contribution of this paper is Marine Multi-Objective Compliance-Integrated Coevolution (MMOCIC), a framework that blends team-wide optimization with established norms for real-world deployments of learning-based coordination.
