移动机器人对气体泄漏源的定位—–矩阵半张量积方法

Mobile robot gas source localization: a semi-tensor product approach

中文关键词  矩阵半张量积  视嗅觉融合  机器人  气体泄漏源定位

英文关键词  semi-tensor product of matrices  fusion of vision and olfaction  mobile robot  gas source localization

中文摘要

      对于使用移动机器人在风速/风向变化较大的气流环境中定位气体泄漏源的问题, 我们建立了一个定位模 型. 模型的输入为机器人在定位过程中实时获取的多传感器信息(激光信息、视觉信息、气体浓度信息、风信息等), 输出为相应的搜寻行为或策略, 主要包括避障行为、随机搜寻、视觉搜寻、化学趋向性搜寻、风趋向性搜寻、路径规 划和气体泄漏源定位等. 利用矩阵的半张量积理论, 我们确定了这个模型输入和输出之间的结构矩阵. 根据多传感 器的测量信息, 结构矩阵产生相应的搜寻行为或策略, 由动态机器人有效地完成, 以确定气体源的位置. 本方法的可 靠性经过机器人实地实验得到验证.

英文摘要

      We build the localization model for a mobile robot in locating the gas source in the airflow environments where both the wind speed and direction have relatively large-scale fluctuation. The inputs to the localization model are multi-sensor information, such as vision, olfaction and wind information，and so on. The outputs are the corresponding searching behaviors/methods including the avoiding behavior, random searching, visual searching, chemotaxis searching, anemotaxis searching, path planning and gas source declaration, and so forth. A structural matrix of the localization model is set up based on the semi-tensor product theory. According to the measured information from multi-sensor, this structural matrix generates the corresponding searching behaviors/methods that will be efficiently carried out by the mobile robot to locate the gas source. The reliability of the proposed model is validated by real robot experiments.