发表机构
Technological University of Uruguay（乌拉圭理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出情境感知前沿优先方法，在Gazebo仿真的两类室内救援场景中，该方法较其他方法实现最高完成率与幸存者回收率，适用于复杂救援场景的平衡决策。
AI 中文摘要
四足机器人是搜索与救援任务的有潜力平台，因为它们能在杂乱的室内环境中移动，而这类环境可能对轮式系统构成限制。然而，在未知的救援场景中，自主探索必须在地图扩展与发现幸存者的可能性之间取得平衡，这是经典前沿选择策略未明确解决的问题。本文提出一种面向单机器人四足搜索与救援的情境感知前沿优先方法。该方法保留了前沿探索框架，但通过信息增益、观测不足、救援相关性、地形惩罚和行进成本扩展了前沿排序。该方法在Gazebo仿真中，使用四足机器人在两个不同难度级别的室内救援场景中进行评估。第一个场景用于合理性检查，第二个场景则引入更严重的杂乱和前沿歧义。实验结果表明，所有方法在简单场景中表现可靠，而在复杂场景中表现不同。在该场景中，所提方法在评估方法中实现了最高的完成率和最高的幸存者回收率。这些结果表明，当前沿选择变得复杂，且必须在通用探索目标与救援效用之间取得平衡时，情境感知前沿优先策略是有益的。
英文摘要
Quadruped robots are a promising platform for search and rescue missions because they can navigate cluttered indoor environments that may be restrictive for wheeled systems. However, in unknown rescue scenarios, autonomous exploration must balance map expansion with the likelihood of finding victims, which is not explicitly addressed by clas- sical frontier selection strategies. This paper presents a situation aware frontier prioritization method for single robot quadruped search and rescue. The proposed approach preserves the frontier exploration framework, but extends frontier ranking with information gain, observation deficit, rescue relevance, terrain penalty, and travel cost. The method is eval- uated in Gazebo simulation with a quadruped robot in two indoor rescue scenarios with different levels of difficulty. The first scenario is used as a sanity check, while the second introduces stronger clutter and frontier ambiguity. Experimental results show that all methods perform reliably in a simple scenario, whereas in a complex scenario is different. In that setting, the proposed method achieves the highest completion rate and the highest victim recovery among the evaluated approaches. These results indicate that situation aware frontier prioritization is beneficial when frontier choice becomes nontrivial and rescue utility must be balanced against generic exploration objectives.
