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山东大学学报 (工学版) ›› 2019, Vol. 49 ›› Issue (6): 45-54.doi: 10.6040/j.issn.1672-3961.0.2018.495

• 控制科学与工程——机器人专题 • 上一篇    下一篇

智能家庭中一种基于本体的机器人服务认知机制

孔令龙(),田国会*()   

  1. 山东大学控制科学与工程学院, 山东 济南 250061
  • 收稿日期:2018-11-22 出版日期:2019-12-20 发布日期:2019-12-17
  • 通讯作者: 田国会 E-mail:linglong_kong@mail.sdu.edu.cn;g.h.tian@sdu.edu.cn
  • 作者简介:孔令龙(1994—),男,山东菏泽人,硕士研究生,主要研究方向为本体技术,服务任务认知.E-mail:linglong_kong@mail.sdu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(61773239);山东省自然科学基金资助项目(ZR2015FM007)

A robot service recognition mechanism based on ontology in smart home

Linglong KONG(),Guohui TIAN*()   

  1. School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China
  • Received:2018-11-22 Online:2019-12-20 Published:2019-12-17
  • Contact: Guohui TIAN E-mail:linglong_kong@mail.sdu.edu.cn;g.h.tian@sdu.edu.cn
  • Supported by:
    国家自然科学基金资助项目(61773239);山东省自然科学基金资助项目(ZR2015FM007)

摘要:

为增强机器人提供不同类型服务的能力,针对智能家庭环境中的服务机器人提出一种基于语义网规则语言的机器人分类服务推理方法。利用本体技术建立智能家庭的本体模型,通过该模型集成来自不同数据源的数据,消除设备之间的异构性。根据智能家庭机器人服务系统的服务特点划分服务类型,利用历史上下文信息生成服务规则库。通过推理引擎匹配实时的上下文信息与服务规则实现机器人的服务推理。智能家庭背景下的系统运行试验结果表明,机器人服务推理方法能够完成智能家庭环境中不同类型的服务推理,从而进一步提高机器人服务的智能性。

关键词: 服务机器人, 本体模型, 智能家庭, 语义网, 服务推理

Abstract:

In order to enhance the ability of robots to provide different types of services, a classification service reasoning method based on semantic web rule language was proposed for service robots in smart home environments. The ontology model of smart home was established by ontology technology, which integrated data from different data sources and eliminated the heterogeneity between devices. The classification of service types were based on the service characteristics of robot service system in smart home. With historical context information, the service rule bases were set up. The reasoning engine could match the real-time context information and service rules to realize the service reasoning of the robot. The experimental results showed that the robot service reasoning method could achieve different types of service reasoning in smart home environments and further improve the intelligence of the robot service.

Key words: service robot, ontology model, smart home, semantic web, service reasoning

中图分类号: 

  • TP242.6

图1

机器人服务系统架构"

图2

基于OWL的本体模型分层结构"

图3

基于OWL的智能家庭本体关系"

图4

SSN本体模块结构"

图5

传感器数据映射"

表1

基于人行为习惯的服务类型"

序号 条件 服务类型
1 (U1U2Se1Se2) & (U1=U2Se1=Se2) U
2 (Su1Su2Se1Se2) & (Su1=Su2Se1=Se2) Su
3 (Lu1Lu2Se1Se2) & (Lu1=Lu2Se1=Se2) Lu
4 (αηSe1Se2) & (α < ηSe1=Se2) Time
5 (U1U2, Su1Su2Se1Se2) & (U1=U2, Su1=Su2Se1=Se2) U-Su
6 (U1U2, Lu1Lu2Se1Se2) & (U1=U2, Lu1=Lu2Se1=Se2) U-Lu
7 (U1U2, αηSe1Se2) & (U1=U2, α < ηSe1=Se2) U-Time
8 (Su1Su2, Lu1Lu2Se1Se2) & (Su1=Su2, Lu1=Lu2Se1=Se2) Su-Lu
9 (Su1Su2, αηSe1Se2) & (Su1=Su2, α < ηSe1=Se2) Su-Time
10 (Lu1Lu2, αηSe1Se2) & (Lu1=Lu2, α < ηSe1=Se2) Lu-Time
11 (U1U2, Su1Su2, Lu1Lu2Se1Se2) & (U1=U2, Su1=Su2, Lu1=Lu2Se1=Se2) U-Su-Lu
12 (U1U2, Su1Su2, αηSe1Se2) & (U1=U2, Su1=Su2, α < ηSe1=Se2) U-Su-Time
13 (U1U2, Lu1Lu2, αηSe1Se2) & (U1=U2, Lu1= Lu2, α < ηSe1=Se2) U-Lu-Time
14 (Su1Su2, Lu1Lu2, αηSe1Se2) & (Su1=Su2, Lu1=Lu2, α < ηSe1=Se2) Su-Lu-Time
15 (U1U2, Su1Su2, Lu1Lu2, αηSe1Se2) & (U1=U2, Su1=Su2, Lu1=Lu2, α < ηSe1=Se2) U-Su-Lu-Time

图6

SWRL服务规则生成"

图7

服务推理过程"

表2

测试场景实时信息"

主体 属性 客体
Alan hasUserState sit
Alan hasLocation bedroom
sit hasTime 19:00
Bill hasUserState sit
Bill hasLocation livingroom
sit hasTime 19:00
bread1 hasItemsState cooled
bread1 hasLocation table 1
cooled hasTime 19:00

图8

信息映射试验结果"

图9

服务规则生成时间比较"

图10

机器人实验平台"

表3

SWRL服务规则"

规则名规则表示
Rule-1User(Alan)∧StateUser(sit)∧Location(bedroom)∧Time(t1)∧hasUserState(Alan, sit)∧hasLocation(Alan, bedroom)∧hasTime(sit, t1)→operateOn(drink, coffee)
Rule-2User(Alan)∧StateUser(sit)∧Location(bedroom)∧Time(t2)∧hasUserState(Alan, sit)∧hasLocation(Alan, bedroom)∧hasTime(sit, t2)→operateOn(drink, water)
Rule-3User(Bill)∧StateUser(sit)∧Location(bedroom)∧Time(t1)∧hasUserState(Bill, sit)∧hasLocation(Bill, bedroom)∧hasTime(sit, t1)→operateOn(drink, water)
Rule-4User(Bill)∧StateUser(sit)∧Location(livingroom)∧Time(t2)∧hasUserState(Bill, wake)∧hasLocation(Bill, livingroom)∧hasTime(sit, t2)→operateOn(ON, tv)
Rule-5User(Bill)∧StateUser(wake)∧Location(bedroom)∧Time(t3)∧hasUserState(Bill, wake)∧hasLocation(Bill, bedroom)∧hasTime(wake, t3)→operateOn(open, window1)
Rule-6User(Bill)∧StateUser(sleep)∧Location(bedroom)∧Time(t4)∧hasUserState(Bill, sleep)∧hasLocation(Bill, bedroom)∧hasTime(sleep, t4)→operateOn(close, window1)
Rule-7Items(book1)∧StateItems(on)∧Location(floor)∧Time(t5)∧hasItemsState(book1, on)∧hasLocation(book1, floor)∧hasTime(on, t5)→operateOn(pick, book1)
Rule-8Items(bread1)∧StateItems(cooled)∧Location(table 1)∧Time(t6)∧hasItemsState(bread1, cooled)∧hasLocation(bread1, table 1)∧hasTime(cooled, t6)→operateOn(heat, bread1)
Rule-9User(Alan)∧Location(bedroom)∧Environment(temsensor1)∧Time(t7)∧hasLocation(Alan, bedroom)∧hasLocation(aircondition1, bedroom)∧hasTime(temsensor1, t7)∧hasEnvironment(aircondition1, temsensor1)∧value(temsensor1, 28)→operateOn(adjust, aircondition1)∧value(aircondition1, 25)
Rule-10User(Alan)∧Location(bedroom)∧Environment(temsensor1)∧Time(t8)∧hasLocation(Alan, bedroom)∧hasLocation(aircondition1, bedroom)∧hasTime(temsensor1, t8)∧hasEnvironment(aircondition1, temsensor1)∧value(temsensor1, 16)→operateOn(adjust, aircondition1)∧value(aircondition1, 22)

图11

服务推理过程"

图12

机器人服务执行结果"

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