Chemical, biological, or radioactive substances may be released in accidents, posing a threat to human life and property. Due to the dense obstacles and specific structures of indoor environments, indoor source searching still faces challenges, such as the initial position of the robot cannot be placed freely, the source may not be in the airflow, and most areas indoors lack concentration and airflow clues. This study proposes an exploration-enhanced search algorithm, enabling the robot to search for a source located downstream of the robot or outside the airflow in an indoor environment with a narrow plume without losing the classic upstream search ability. The algorithm equips the robot with the capability to search for a source in complex indoor environments where measurements frequently change. The algorithm is evaluated in the simulated environment to assess the contributions of its components and its performance under different airflow speeds. The algorithm is also compared with the state-of-the-art algorithms and shows superior performance. The effectiveness of the algorithm is further demonstrated in real-world environments.

中文翻译：

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一种用于机器人室内源搜索的探索增强搜索算法


事故中可能会释放出化学、生物或放射性物质，对人类生命和财产造成威胁。由于室内环境障碍物密集、结构特殊，室内寻源仍面临挑战，如机器人初始位置无法自由放置、声源可能不在气流中、室内大部分区域缺乏注意力和气流线索等。 。本研究提出了一种探索增强型搜索算法，使机器人能够在羽流狭窄的室内环境中搜索位于机器人下游或气流外部的源，而不会失去经典的上游搜索能力。该算法使机器人能够在测量结果经常变化的复杂室内环境中搜索信号源。该算法在模拟环境中进行评估，以评估其组件的贡献及其在不同气流速度下的性能。该算法还与最先进的算法进行了比较，显示出优越的性能。该算法的有效性在现实环境中得到了进一步证明。