路飞, 刘硕, 田国会. 智能机器人服务环境下传感数据映射及服务组合方法研究[J]. 机器人, 2019, 41(1): 30-39. DOI: 10.13973/j.cnki.robot.18055
引用本文: 路飞, 刘硕, 田国会. 智能机器人服务环境下传感数据映射及服务组合方法研究[J]. 机器人, 2019, 41(1): 30-39. DOI: 10.13973/j.cnki.robot.18055
LU Fei, LIU Shuo, TIAN Guohui. Methods for Sensor Data Mapping and Automatic Service Composition in Intelligent Robot Service Environment[J]. ROBOT, 2019, 41(1): 30-39. DOI: 10.13973/j.cnki.robot.18055
Citation: LU Fei, LIU Shuo, TIAN Guohui. Methods for Sensor Data Mapping and Automatic Service Composition in Intelligent Robot Service Environment[J]. ROBOT, 2019, 41(1): 30-39. DOI: 10.13973/j.cnki.robot.18055

智能机器人服务环境下传感数据映射及服务组合方法研究

Methods for Sensor Data Mapping and Automatic Service Composition in Intelligent Robot Service Environment

  • 摘要: 为了提高传感器数据信息可利用性和机器人服务的智能性,针对动态异构智能空间提出基于SSN(语义传感器网络)本体的传感器数据映射方法和Web服务组合方法.首先,利用SSN本体技术建立智能空间中的传感器数据本体模型,通过传感器标注和语义映射语言(SASML)自动将动态传感器数据映射进SSN本体文件,实现物理-信息的转换.在此基础上,利用面向服务计算的思想,采用Web服务技术将空间设备功能封装成统一的接口,建立智能空间服务模型.最后,采用无回溯反向链(NBBC)算法实现动态Web服务组合,以实现提供复杂服务的能力.智能空间背景下的系统运行实验结果表明,构建的SSN本体模型能够有效融合传感器数据信息,实现的服务组合算法能够将单个简单服务组件组合成具有复杂功能的服务序列,从而进一步提高机器人服务的智能性.

     

    Abstract: In order to improve the availability of sensor data and intelligence of robot service, methods for sensor data mapping based on SSN (semantic sensor network) ontology and for Web service composition in dynamic heterogeneous intelligent service environment are proposed. Firstly, a sensor data ontology model in intelligent space is established using SSN ontology technology. The sensor annotation and semantic mapping language (SASML) is adopted to map dynamic sensor data into SSN ontology files automatically, and conversion of the physical information into cyber information is realized. On this basis, with the theory of service-oriented computing, intelligent space service model can be realized by the Web services which will package heterogeneous devices into unified function interfaces. Finally, dynamic Web service composition is implemented using the non-backtrace backward chaining (NBBC) algorithm to provide complex services for users. The experimental results in intelligent space show that the SSN ontology model constructed can effectively integrate sensor data information, and the service composition algorithm to combine single simple service components into complex service sequences can significantly improve the intelligence of robot services.

     

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