路飞, 田国会, 李擎. 智能空间环境下基于本体的机器人服务自主认知及规划[J]. 机器人, 2017, 39(4): 423-430. DOI: 10.13973/j.cnki.robot.2017.0423
引用本文: 路飞, 田国会, 李擎. 智能空间环境下基于本体的机器人服务自主认知及规划[J]. 机器人, 2017, 39(4): 423-430. DOI: 10.13973/j.cnki.robot.2017.0423
LU Fei, TIAN Guohui, LI Qing. Autonomous Cognition and Planning of Robot Service Based on Ontology in Intelligent Space Environment[J]. ROBOT, 2017, 39(4): 423-430. DOI: 10.13973/j.cnki.robot.2017.0423
Citation: LU Fei, TIAN Guohui, LI Qing. Autonomous Cognition and Planning of Robot Service Based on Ontology in Intelligent Space Environment[J]. ROBOT, 2017, 39(4): 423-430. DOI: 10.13973/j.cnki.robot.2017.0423

智能空间环境下基于本体的机器人服务自主认知及规划

Autonomous Cognition and Planning of Robot Service Based on Ontology in Intelligent Space Environment

  • 摘要: 为了提高机器人服务的自主性,针对动态家庭环境提出基于本体的机器人服务自主认知及规划方法.首先,利用本体技术为智能空间系统建立本体模型,并通过构建语义规则的方法,建立以用户为中心自适应调整的数据-概念转换机制,实现智能空间信息的整合.在此基础上,建立服务任务推理规则库对本体模型进行扩展,通过匹配实时更新的智能空间本体与规则库中的知识,推理出机器人需要执行的服务序列,实现机器人对用户所需服务的自主认知.最后,利用分层任务网络的思想,在JSHOP2规划器上实现服务任务的具体规划.智能空间环境下的任务执行实验结果表明,利用该方法服务机器人能够根据环境信息和用户信息实现对任务的自主认知,进而主动地为用户提供个性化的服务,其服务的智能化水平得以显著提高.

     

    Abstract: In order to improve the autonomy of robot service, an autonomous ontology-based cognition and planning method for robot service in dynamic home environments is presented. Firstly, the ontology model of the intelligent space is established based on ontology technology. And the user-centered adaptive data-concept conversion mechanism is established after the semantic rules are set up, to integrate the information of intelligent space. Based on these, the inference rule base for service task can be constructed to realize the expansion of the ontology model, and the intelligent space ontology updated in real time is matched with the rule base in order to generate the service sequence of the robot. Finally, the idea of hierarchical task network is used to realize the task planning in JSHOP2 planner. Results of the task planning experiment in intelligent space environment show that the service robot can realize the autonomous cognition in the service task according to the environment and the user's information, and provide personalized services for the user actively. The intelligence level of service can be significantly improved.

     

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