Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (6): 45-54.doi: 10.6040/j.issn.1672-3961.0.2018.495

• Control Science & Engineering - Special Topic on Robot • Previous Articles     Next Articles

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)

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

CLC Number: 

  • TP242.6

Fig.1

Service system architecture of robot"

Fig.2

Ontology model layered structure based on OWL"

Fig.3

OWL-based ontology relationship in smart home"

Fig.4

The SSN ontology module structure"

Fig.5

Sensor data mapping process"

Table 1

The types of service based on human behavior"

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

Fig.6

The generation of SWRL service rule"

Fig.7

The process of service reasoning"

Table 2

Real-time information of test scenario"

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

Fig.8

The experimental results of information mapping"

Fig.9

The comparison of service rule generation time"

Fig.10

Experimental platform of the robot"

Table 3

SWRL service rules"

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)

Fig.11

Process of service reasoning"

Fig.12

Execution result of robot service"

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