Knowledge processing for robots - Revision history

Jarble: link open-world assumption using Find link

2021-05-22T02:13:23Z

link open-world assumption using Find link

← Previous revision		Revision as of 02:13, 22 May 2021
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	To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.		To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.

	KnowRob adopts the [[closed-world assumption]] Prolog, and an open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.		KnowRob adopts the [[closed-world assumption]] Prolog, and an [[open-world assumption]] by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.
	</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.		</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.

Jarble: link closed-world assumption using Find link

2021-05-22T02:13:06Z

link closed-world assumption using Find link

← Previous revision		Revision as of 02:13, 22 May 2021
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	To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.		To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.

	KnowRob adopts the closed-world assumption Prolog, and an open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.		KnowRob adopts the [[closed-world assumption]] Prolog, and an open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.
	</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.		</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.

Cewbot: Normalize {{Multiple issues}}: Remove {{Multiple issues}} for only 1 maintenance template(s): Lead too short

2020-06-01T04:08:23Z

Normalize {{Multiple issues}}: Remove {{Multiple issues}} for only 1 maintenance template(s): Lead too short

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	{{short description\|Knowledge representation framework}}		{{short description\|Knowledge representation framework}}
	{{Multiple issues\|
	{{Orphan\|date=December 2019}}		{{Orphan\|date=December 2019}}
	{{lead too short\|date=November 2018}}		{{lead too short\|date=November 2018}}
	}}

	'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].		'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].

Sun Creator: General fixes, added orphan tag, typo(s) fixed: a OWL → an OWL (2)

2019-12-12T01:15:38Z

General fixes, added orphan tag, typo(s) fixed: a OWL → an OWL (2)

← Previous revision		Revision as of 01:15, 12 December 2019
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	{{short description\|Knowledge representation framework}}		{{short description\|Knowledge representation framework}}
	{{Multiple issues\|		{{Multiple issues\|
			{{Orphan\|date=December 2019}}
	{{lead too short\|date=November 2018}}		{{lead too short\|date=November 2018}}
	}}		}}

	'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].		'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].

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	KnowRob has been used by different research groups, as the [[Rice University]] using the ontological knowledge base in a robotic platform.<ref>Z. Saigol, M. Wang, B. Ridder and D. M. Lane (2015) The Benefits of Explicit Ontological Knowledge-Bases for Robotic Systems. Towards Autonomous Robotic Systems: 229-235. {{ISBN\|978-3-319-22416-9}}.</ref> As well by the [[Eindhoven University of Technology]] research group competing in the [[RoboCup]] league, in the "at Home" category, with the RoboEarth project.		KnowRob has been used by different research groups, as the [[Rice University]] using the ontological knowledge base in a robotic platform.<ref>Z. Saigol, M. Wang, B. Ridder and D. M. Lane (2015) The Benefits of Explicit Ontological Knowledge-Bases for Robotic Systems. Towards Autonomous Robotic Systems: 229-235. {{ISBN\|978-3-319-22416-9}}.</ref> As well by the [[Eindhoven University of Technology]] research group competing in the [[RoboCup]] league, in the "at Home" category, with the RoboEarth project.

	As well, KnowRob is mentioned in the work of some research groups from the [[Lucian Blaga University of Sibiu]],<ref>Flaviu Constantin and Florin Constantin (2017) Collaborative Robots and Knowledge Management - A Short Review. Acta Uiversitatis Cibiniensis – Technical Series. De Gruyter Open LXIX: 143-147. {{doi\|10.1515/aucts-2017-0018}}</ref> [[Middle East Technical University]] in their combination of different knowledge bases,<ref>Ilker Bozcan and Sinan Kalkan (2017) Combining Different Knowledge-bases into a Single Partially-grounded Robotic Knowledge-base. Technical report METU-CENG-TR-2017-02:1-9. Middle East Technical University, Turkey</ref> [[Keio University]] as related work because of the ontology service,<ref>Mori Yuichiro, Ogawa Yuhei, Hikawa Akatsuki and Yamaguchi Takahira (2014) Multi-robot Coordination Based on Ontologies and Semantic Web Service. Knowledge Management and Acquisition for Smart Systems and Services:150-164. {{ISBN\|978-3-319-13332-4}}. {{doi\|10.1007/978-3-319-13332-4_13}}</ref> [[University of Texas at Austin]] as related work as well because of the relation with the work presented,<ref>Priyanka Khante and Andrea Thomaz. Situating Abstract Knowledge via Human Verification.</ref> [[Hanyang University]] as related work as a OWL based knowledge processing framework.<ref>Keon Kim, Doo Soo Chang and Yong Suk Choi (2017) Ontology based Human-Robot Interaction Knowledge for Intelligent Services. ICSR2017 Workshop on Social Human-Robot Interaction of Service Robots.</ref>		As well, KnowRob is mentioned in the work of some research groups from the [[Lucian Blaga University of Sibiu]],<ref>Flaviu Constantin and Florin Constantin (2017) Collaborative Robots and Knowledge Management - A Short Review. Acta Uiversitatis Cibiniensis – Technical Series. De Gruyter Open LXIX: 143-147. {{doi\|10.1515/aucts-2017-0018}}</ref> [[Middle East Technical University]] in their combination of different knowledge bases,<ref>Ilker Bozcan and Sinan Kalkan (2017) Combining Different Knowledge-bases into a Single Partially-grounded Robotic Knowledge-base. Technical report METU-CENG-TR-2017-02:1-9. Middle East Technical University, Turkey</ref> [[Keio University]] as related work because of the ontology service,<ref>Mori Yuichiro, Ogawa Yuhei, Hikawa Akatsuki and Yamaguchi Takahira (2014) Multi-robot Coordination Based on Ontologies and Semantic Web Service. Knowledge Management and Acquisition for Smart Systems and Services:150-164. {{ISBN\|978-3-319-13332-4}}. {{doi\|10.1007/978-3-319-13332-4_13}}</ref> [[University of Texas at Austin]] as related work as well because of the relation with the work presented,<ref>Priyanka Khante and Andrea Thomaz. Situating Abstract Knowledge via Human Verification.</ref> [[Hanyang University]] as related work as an OWL based knowledge processing framework.<ref>Keon Kim, Doo Soo Chang and Yong Suk Choi (2017) Ontology based Human-Robot Interaction Knowledge for Intelligent Services. ICSR2017 Workshop on Social Human-Robot Interaction of Service Robots.</ref>

	== Representations ==		== Representations ==
	To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.		To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.

	KnowRob adopts the closed-world assumption Prolog, and a open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.		KnowRob adopts the closed-world assumption Prolog, and an open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.
	</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.		</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.

Jarble: adding DOI links

2019-11-28T16:01:12Z

adding DOI links

← Previous revision		Revision as of 16:01, 28 November 2019
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	== The framework ==		== The framework ==
	KnowRob can serve as a [[common sense]] framework for the integration of knowledge. This knowledge can be static encyclopedic knowledge, common sense knowledge, task descriptions, environment models, object information, observed actions, etc., which can come from different sources, like manually axiomatized, derived from observations, or imported from the web.<ref>M. Tenorth and M. Beetz (2017) [http://www.sciencedirect.com/science/article/pii/S0004370215000843 Representations for robot knowledge in the knowrob framework]. Artificial Intelligence: Supplement C 247: 151-169. {{ISSN\|0004-3702}}. doi:10.1016/j.artint.2015.05.010. Special Issue on AI and Robotics.</ref>		KnowRob can serve as a [[common sense]] framework for the integration of knowledge. This knowledge can be static encyclopedic knowledge, common sense knowledge, task descriptions, environment models, object information, observed actions, etc., which can come from different sources, like manually axiomatized, derived from observations, or imported from the web.<ref>M. Tenorth and M. Beetz (2017) [http://www.sciencedirect.com/science/article/pii/S0004370215000843 Representations for robot knowledge in the knowrob framework]. Artificial Intelligence: Supplement C 247: 151-169. {{ISSN\|0004-3702}}. {{doi\|10.1016/j.artint.2015.05.010}}. Special Issue on AI and Robotics.</ref>

	KnowRob has been used by different research groups, as the [[Rice University]] using the ontological knowledge base in a robotic platform.<ref>Z. Saigol, M. Wang, B. Ridder and D. M. Lane (2015) The Benefits of Explicit Ontological Knowledge-Bases for Robotic Systems. Towards Autonomous Robotic Systems: 229-235. {{ISBN\|978-3-319-22416-9}}.</ref> As well by the [[Eindhoven University of Technology]] research group competing in the [[RoboCup]] league, in the "at Home" category, with the RoboEarth project.		KnowRob has been used by different research groups, as the [[Rice University]] using the ontological knowledge base in a robotic platform.<ref>Z. Saigol, M. Wang, B. Ridder and D. M. Lane (2015) The Benefits of Explicit Ontological Knowledge-Bases for Robotic Systems. Towards Autonomous Robotic Systems: 229-235. {{ISBN\|978-3-319-22416-9}}.</ref> As well by the [[Eindhoven University of Technology]] research group competing in the [[RoboCup]] league, in the "at Home" category, with the RoboEarth project.

	As well, KnowRob is mentioned in the work of some research groups from the [[Lucian Blaga University of Sibiu]],<ref>Flaviu Constantin and Florin Constantin (2017) Collaborative Robots and Knowledge Management - A Short Review. Acta Uiversitatis Cibiniensis – Technical Series. De Gruyter Open LXIX: 143-147. doi:10.1515/aucts-2017-0018</ref> [[Middle East Technical University]] in their combination of different knowledge bases,<ref>Ilker Bozcan and Sinan Kalkan (2017) Combining Different Knowledge-bases into a Single Partially-grounded Robotic Knowledge-base. Technical report METU-CENG-TR-2017-02:1-9. Middle East Technical University, Turkey</ref> [[Keio University]] as related work because of the ontology service,<ref>Mori Yuichiro, Ogawa Yuhei, Hikawa Akatsuki and Yamaguchi Takahira (2014) Multi-robot Coordination Based on Ontologies and Semantic Web Service. Knowledge Management and Acquisition for Smart Systems and Services:150-164. {{ISBN\|978-3-319-13332-4}}. doi:10.1007/978-3-319-13332-4_13</ref> [[University of Texas at Austin]] as related work as well because of the relation with the work presented,<ref>Priyanka Khante and Andrea Thomaz. Situating Abstract Knowledge via Human Verification.</ref> [[Hanyang University]] as related work as a OWL based knowledge processing framework.<ref>Keon Kim, Doo Soo Chang and Yong Suk Choi (2017) Ontology based Human-Robot Interaction Knowledge for Intelligent Services. ICSR2017 Workshop on Social Human-Robot Interaction of Service Robots.</ref>		As well, KnowRob is mentioned in the work of some research groups from the [[Lucian Blaga University of Sibiu]],<ref>Flaviu Constantin and Florin Constantin (2017) Collaborative Robots and Knowledge Management - A Short Review. Acta Uiversitatis Cibiniensis – Technical Series. De Gruyter Open LXIX: 143-147. {{doi\|10.1515/aucts-2017-0018}}</ref> [[Middle East Technical University]] in their combination of different knowledge bases,<ref>Ilker Bozcan and Sinan Kalkan (2017) Combining Different Knowledge-bases into a Single Partially-grounded Robotic Knowledge-base. Technical report METU-CENG-TR-2017-02:1-9. Middle East Technical University, Turkey</ref> [[Keio University]] as related work because of the ontology service,<ref>Mori Yuichiro, Ogawa Yuhei, Hikawa Akatsuki and Yamaguchi Takahira (2014) Multi-robot Coordination Based on Ontologies and Semantic Web Service. Knowledge Management and Acquisition for Smart Systems and Services:150-164. {{ISBN\|978-3-319-13332-4}}. {{doi\|10.1007/978-3-319-13332-4_13}}</ref> [[University of Texas at Austin]] as related work as well because of the relation with the work presented,<ref>Priyanka Khante and Andrea Thomaz. Situating Abstract Knowledge via Human Verification.</ref> [[Hanyang University]] as related work as a OWL based knowledge processing framework.<ref>Keon Kim, Doo Soo Chang and Yong Suk Choi (2017) Ontology based Human-Robot Interaction Knowledge for Intelligent Services. ICSR2017 Workshop on Social Human-Robot Interaction of Service Robots.</ref>

	== Representations ==		== Representations ==
	To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.		To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.

	KnowRob adopts the closed-world assumption Prolog, and a open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. doi:10.1177/0278364913481635.		KnowRob adopts the closed-world assumption Prolog, and a open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.
	</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.		</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.

Lizyazpin at 12:52, 4 October 2019

2019-10-04T12:52:20Z

← Previous revision		Revision as of 12:52, 4 October 2019
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	{{Multiple issues\|		{{Multiple issues\|
	{{lead too short\|date=November 2018}}		{{lead too short\|date=November 2018}}
	{{orphan\|date=November 2018}}
	}}		}}
	'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].		'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].

Lizyazpin at 12:51, 4 October 2019

2019-10-04T12:51:29Z

← Previous revision		Revision as of 12:51, 4 October 2019
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	{{orphan\|date=November 2018}}		{{orphan\|date=November 2018}}
	}}		}}
	'''KnowRob''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].		'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].

	== The framework ==		== The framework ==

PkbwcgsBot: v2.0b - (Task 11 - Approved BRFA) - WP:WCW project (Heading hierarchy)

2019-01-22T17:21:29Z

v2.0b - (Task 11 - Approved BRFA) - WP:WCW project (Heading hierarchy)

← Previous revision		Revision as of 17:21, 22 January 2019
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	In its second version, KnowRob provides a logic interface to the hybrid reasoning kernel as a logic based language. This language presents the hybrid reasoning kernel as if everything were entities retrievable by providing partial descriptions for them. This entities descriptions include objects, their parts, and articulation models, environments composed of objects, software components, actions, and events.		In its second version, KnowRob provides a logic interface to the hybrid reasoning kernel as a logic based language. This language presents the hybrid reasoning kernel as if everything were entities retrievable by providing partial descriptions for them. This entities descriptions include objects, their parts, and articulation models, environments composed of objects, software components, actions, and events.

	==== Episodic memories ====		=== Episodic memories ===
	[[Episodic memory]] is related to the experience information, which is organized temporally and spatially, alongside combined with context information. In KnowRob, an episodic memory is understood as a recording that the agent makes of the ongoing activity, which includes very detailed information about the actions, motions, their purposes, effects and the behavior they generate, it also includes the images captured during execution, etc.<ref>M. Beetz, D. Bessler, A. Haidu, M. Pomarlan, A. K. Bozcuoglu and G. Bartels (2018) KnowRob 2.0 -- A 2nd Generation Knowledge Processing Framework for Cognition-enabled Robotic Agents. International Conference on Robotics and Automation (ICRA).</ref>		[[Episodic memory]] is related to the experience information, which is organized temporally and spatially, alongside combined with context information. In KnowRob, an episodic memory is understood as a recording that the agent makes of the ongoing activity, which includes very detailed information about the actions, motions, their purposes, effects and the behavior they generate, it also includes the images captured during execution, etc.<ref>M. Beetz, D. Bessler, A. Haidu, M. Pomarlan, A. K. Bozcuoglu and G. Bartels (2018) KnowRob 2.0 -- A 2nd Generation Knowledge Processing Framework for Cognition-enabled Robotic Agents. International Conference on Robotics and Automation (ICRA).</ref>

Lizyazpin at 16:18, 3 December 2018

2018-12-03T16:18:15Z

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	{{short description\|Knowledge representation framework}}		{{short description\|Knowledge representation framework}}
	{{Multiple issues\|		{{Multiple issues\|
	{{primary sources\|date=November 2018}}
	{{lead too short\|date=November 2018}}		{{lead too short\|date=November 2018}}
	{{orphan\|date=November 2018}}		{{orphan\|date=November 2018}}

Lizyazpin: /* Representations */

2018-12-03T16:17:14Z

Representations

← Previous revision		Revision as of 16:17, 3 December 2018
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	KnowRob adopts the closed-world assumption Prolog, and a open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. doi:10.1177/0278364913481635.		KnowRob adopts the closed-world assumption Prolog, and a open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. doi:10.1177/0278364913481635.
	</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.<ref>M. Tenorth, G. Bartels, and M. Beetz (2014) Knowledge-based specification of robot motions. Twenty-first European Conference on Artificial Intelligence (ECAI):873-878. Amsterdam, The Netherlands. {{ISBN\|978-1-61499-418-3}}. doi:10.3233/978-1-61499-419-0-873</ref>		</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.

	In its second version, KnowRob provides a logic interface to the hybrid reasoning kernel as a logic based language. This language presents the hybrid reasoning kernel as if everything were entities retrievable by providing partial descriptions for them. This entities descriptions include objects, their parts, and articulation models, environments composed of objects, software components, actions, and events.		In its second version, KnowRob provides a logic interface to the hybrid reasoning kernel as a logic based language. This language presents the hybrid reasoning kernel as if everything were entities retrievable by providing partial descriptions for them. This entities descriptions include objects, their parts, and articulation models, environments composed of objects, software components, actions, and events.

← Previous revision		Revision as of 01:15, 12 December 2019
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	{{short description\|Knowledge representation framework}}		{{short description\|Knowledge representation framework}}
	{{Multiple issues\|		{{Multiple issues\|
			{{Orphan\|date=December 2019}}
	{{lead too short\|date=November 2018}}		{{lead too short\|date=November 2018}}
	}}		}}

	'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].		'''[[KnowRob]]''' (Knowledge processing for robots) is a system which combines [[knowledge representation and reasoning]] methods to acquire and ground knowledge. This system is the backbone of openEASE. both under developing at the Institute for Artificial Intelligence at the [[University of Bremen]], [[Germany]].

Line 10:		Line 12:
	KnowRob has been used by different research groups, as the [[Rice University]] using the ontological knowledge base in a robotic platform.<ref>Z. Saigol, M. Wang, B. Ridder and D. M. Lane (2015) The Benefits of Explicit Ontological Knowledge-Bases for Robotic Systems. Towards Autonomous Robotic Systems: 229-235. {{ISBN\|978-3-319-22416-9}}.</ref> As well by the [[Eindhoven University of Technology]] research group competing in the [[RoboCup]] league, in the "at Home" category, with the RoboEarth project.		KnowRob has been used by different research groups, as the [[Rice University]] using the ontological knowledge base in a robotic platform.<ref>Z. Saigol, M. Wang, B. Ridder and D. M. Lane (2015) The Benefits of Explicit Ontological Knowledge-Bases for Robotic Systems. Towards Autonomous Robotic Systems: 229-235. {{ISBN\|978-3-319-22416-9}}.</ref> As well by the [[Eindhoven University of Technology]] research group competing in the [[RoboCup]] league, in the "at Home" category, with the RoboEarth project.

	As well, KnowRob is mentioned in the work of some research groups from the [[Lucian Blaga University of Sibiu]],<ref>Flaviu Constantin and Florin Constantin (2017) Collaborative Robots and Knowledge Management - A Short Review. Acta Uiversitatis Cibiniensis – Technical Series. De Gruyter Open LXIX: 143-147. {{doi\|10.1515/aucts-2017-0018}}</ref> [[Middle East Technical University]] in their combination of different knowledge bases,<ref>Ilker Bozcan and Sinan Kalkan (2017) Combining Different Knowledge-bases into a Single Partially-grounded Robotic Knowledge-base. Technical report METU-CENG-TR-2017-02:1-9. Middle East Technical University, Turkey</ref> [[Keio University]] as related work because of the ontology service,<ref>Mori Yuichiro, Ogawa Yuhei, Hikawa Akatsuki and Yamaguchi Takahira (2014) Multi-robot Coordination Based on Ontologies and Semantic Web Service. Knowledge Management and Acquisition for Smart Systems and Services:150-164. {{ISBN\|978-3-319-13332-4}}. {{doi\|10.1007/978-3-319-13332-4_13}}</ref> [[University of Texas at Austin]] as related work as well because of the relation with the work presented,<ref>Priyanka Khante and Andrea Thomaz. Situating Abstract Knowledge via Human Verification.</ref> [[Hanyang University]] as related work as a OWL based knowledge processing framework.<ref>Keon Kim, Doo Soo Chang and Yong Suk Choi (2017) Ontology based Human-Robot Interaction Knowledge for Intelligent Services. ICSR2017 Workshop on Social Human-Robot Interaction of Service Robots.</ref>		As well, KnowRob is mentioned in the work of some research groups from the [[Lucian Blaga University of Sibiu]],<ref>Flaviu Constantin and Florin Constantin (2017) Collaborative Robots and Knowledge Management - A Short Review. Acta Uiversitatis Cibiniensis – Technical Series. De Gruyter Open LXIX: 143-147. {{doi\|10.1515/aucts-2017-0018}}</ref> [[Middle East Technical University]] in their combination of different knowledge bases,<ref>Ilker Bozcan and Sinan Kalkan (2017) Combining Different Knowledge-bases into a Single Partially-grounded Robotic Knowledge-base. Technical report METU-CENG-TR-2017-02:1-9. Middle East Technical University, Turkey</ref> [[Keio University]] as related work because of the ontology service,<ref>Mori Yuichiro, Ogawa Yuhei, Hikawa Akatsuki and Yamaguchi Takahira (2014) Multi-robot Coordination Based on Ontologies and Semantic Web Service. Knowledge Management and Acquisition for Smart Systems and Services:150-164. {{ISBN\|978-3-319-13332-4}}. {{doi\|10.1007/978-3-319-13332-4_13}}</ref> [[University of Texas at Austin]] as related work as well because of the relation with the work presented,<ref>Priyanka Khante and Andrea Thomaz. Situating Abstract Knowledge via Human Verification.</ref> [[Hanyang University]] as related work as an OWL based knowledge processing framework.<ref>Keon Kim, Doo Soo Chang and Yong Suk Choi (2017) Ontology based Human-Robot Interaction Knowledge for Intelligent Services. ICSR2017 Workshop on Social Human-Robot Interaction of Service Robots.</ref>

	== Representations ==		== Representations ==
	To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.		To represent the knowledge, KnowRob uses the [[Web Ontology Language\|OWL ontology language]] and an extended [[first-order logic]] knowledge representation with computable predicates. To give the order of subactions, KnowRob includes a pair-wise ordering constrain, which gives a partial ordering.

	KnowRob adopts the closed-world assumption Prolog, and a open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.		KnowRob adopts the closed-world assumption Prolog, and an open-world assumption by the use of computables.<ref>M. Tenorth and M. Beetz (2013) Knowrob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32(5):566-590. {{doi\|10.1177/0278364913481635}}.
	</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.		</ref> To include reasoning rules into Prolog, KnowRob uses an inference procedure beyond the capabilities of OWL to extract information about tasks executions.

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