| 引用本文: | 蒋萍,王玉振.移动机器人对气体泄漏源的定位—–矩阵半张量积方法[J].控制理论与应用,2015,32(12):1676~1683.[点击复制] |
| JIANG Ping,WANG Yu-zhen.Mobile robot gas source localization: a semi-tensor product approach[J].Control Theory and Technology,2015,32(12):1676~1683.[点击复制] |
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| 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 |
| 摘要点击 2792 全文点击 1324 投稿时间：2014-12-17 修订日期：2015-07-20 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2015.41176 |
| 2015,32(12):1676-1683 |
| 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 |
| 基金项目 国家自然科学基金项目(61374065, 61403161), 山东省泰山学者基金项目资助. |
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| 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. |
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