Fan Shurui, Hao Dongxia, Sun Xudong, Sultan Yusuf Mohamed, Li Zirui, Xia Kewen
Tianjin Key Laboratory of Electronic Materials Devices, School of Electronic and Information Engineering, Hebei University of Technology, Tianjin 300401, China.
Comput Intell Neurosci. 2020 Aug 25;2020:4159241. doi: 10.1155/2020/4159241. eCollection 2020.
Emergency response to hazardous gases in the environment is an important research field in environmental monitoring. In recent years, with the rapid development of sensor technology and mobile device technology, more autonomous search algorithms for hazardous gas emission sources are proposed in uncertain environment, which can avoid emergency personnel from contacting hazardous gas in a short distance. Infotaxis is an autonomous search strategy without a concentration gradient, which uses scattered sensor data to track the location of the release source in turbulent environment. This paper optimizes the imbalance of exploitation and exploration in the reward function of Infotaxis algorithm and proposes a mobile strategy for the three-dimensional scene. In two-dimensional and three-dimensional scenes, the average steps of search tasks are used as the evaluation criteria to analyze the information trend algorithm combined with different reward functions and mobile strategies. The results show that the balance between the exploitation item and exploration item of the reward function proposed in this paper is better than that of the reward function in the Infotaxis algorithm, no matter in the two-dimensional scenes or in the three-dimensional scenes.
环境中有害气体的应急响应是环境监测中的一个重要研究领域。近年来，随着传感器技术和移动设备技术的快速发展，在不确定环境中提出了更多用于有害气体排放源的自主搜索算法，这可以避免应急人员在短距离内接触有害气体。信息趋化是一种无浓度梯度的自主搜索策略，它利用分散的传感器数据在湍流环境中追踪释放源的位置。本文优化了信息趋化算法奖励函数中开发与探索的不平衡问题，并提出了一种针对三维场景的移动策略。在二维和三维场景中，将搜索任务的平均步数作为评估标准，来分析结合不同奖励函数和移动策略的信息趋化算法。结果表明，无论在二维场景还是三维场景中，本文提出的奖励函数的开发项与探索项之间的平衡都优于信息趋化算法中的奖励函数。
