IEEE: Robotics and automation Society (RAS) Ontologies for Robotics - - PowerPoint PPT Presentation

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IEEE: Robotics and automation Society (RAS) Ontologies for Robotics - - PowerPoint PPT Presentation

Dec 24, 2022 153 likes •363 views

IEEE: Robotics and automation Society (RAS) Ontologies for Robotics and Automation Study group Craig Schlenoff National Institute of Standards and Technology Need A robot can only achieve tasks and perform missions based on what it knows,

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IEEE: Robotics and automation Society (RAS) Ontologies for Robotics and Automation Study group

Craig Schlenoff National Institute of Standards and Technology

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Need

A robot can only achieve tasks and perform missions based on what it knows, which is primarily captured within the robot’s internal knowledge representation. This representation is usually very specialized to the individual robot and often very loosely defined. With the growing complexity of behaviors that robots are expected to perform as well as the need for multi-robot and human-robot collaboration, the need for a standard and well-defined knowledge representation is becoming more evident.

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IEEE Ontologies for Robotics and Automation

Goal

T

  • develop a methodology for knowledge representation and

reasoning in robotics and automation, together with the representation of concepts in an initial set of application domains, to allow for unambiguous knowledge transfer among any group of humans, robots, and other artificial systems.

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Study Group Participants (78 subscribed to mailing list)

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Ground Air Underwater/Surface Space

Scope (Robots)

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Different Kinds of Robotic Knowledge

Cost-based Models LADAR and Color Camera Images Layered Terrain Maps

S3 TentativePlans_Done RoadMarchOrganizationInPlace S4 sp3_ReadyToConductRouteRecon S5 qp_ReadyToOrganizeAA NewCommand S1 MarchOrganizationDetermined S2 CONDUCT TACTICAL ROAD MARCH TO ASSEMBLY AREA S6 qp_ClearOfStartPoint S7 mb_tp_ReconToStartPoint_Done 1 2 14 13 12 11 10 9 8 7 6 5 4 3 15 16 S8 sp3_RouteRecon_Done S9 qp_AtReleasePoint S10 qp_AreaReconOfAADone 17 S11 qp_Status_AssemblyAreaSuitable S14 mb_Unit_AtReleasePoint qp_AssemblyAreaReady S16 mb_Unit_AtReleasePoint S12 mb_Unit_AtStartPoint S12 mb_LastUnit_AtStartPoint S13 tp_TrailPartyAtStartPoint S14 HaltCriteriaMet NewSituationReport NewHigherLevelInformation S15 HaltEnded_ReadyToContinueMarch DisabledVehicleUnscheduledHalt S16 tp_AtReleasePoint S17 mb_tp_OccupyingAssemblyArea S18 AllUnitsSecureInAssemblyArea S4 sp3_PrepareForRouteReconnaissance qp_PrepareToOrganizeAssemblyArea S5 sp3_ConductRouteReconnaissance S6 qp_FollowReconPlatoonToAssemblyArea S1 DetermineMarchColumnOrganization: S2 all_FormTacticalRoadMarchOrganization S3 MakeTentativePlan: Determine_Route, _FireSupport, _MovementFactors, _AA S7 mb_tp_PrepareForRoadMarch S8 PrepareDetailedMovementPlans: S9 sp3_EstablishAssemblyAreaSecurity S10 qp_ConductAreaReconnaissanceOfAA S11 qp_OrganizeAssemblyArea S12 1st_mb_Unit_MoveIntoRoadMarchFormation S16 1st_mb_Unit_OccupyAssemblyArea S16 mb_Unit_OccupyAssemblyArea S12 mb_Unit_ExecuteTacticalRoadMarch next_mb_unit_MoveIntoRoadMarchFormation S13 mb_Unit_ExecuteTacticalRoadMarch tp_MoveIntoRoadMarchFormation S14 tp_SupportMarchColumnMovement S15 mb_tp_ExecuteScheduledHalt UpdateDetailedMovementPlans UpdateDetailedMovementPlans S14 mb_tp_ResumeExecutionOfTacticalRoadMarch S15 mb_tp_ExecuteUnscheduledHalt S17 tp_OccupyAssemblyArea S18 all_FormStandardTroopOrganization S0 TacticalRoadMarchToAssemblyArea_Done 25 24 23 22 21 20 19 18

State Tables Ground Truth

Prediction Equations

Databases

Perception Use Cases Moving Machine

Ontology

Autonomous Vehicle Ontologies

Simulation State Planning Cost Based Planning

Ontology

Judgment Value Prediction Object

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Terms General Logic

Thesauri

formal Taxonomies Frames (OKBC) Data Models (UML, STEP) Description Logics (DAML+OIL)

Principled, informal hierarchies ad hoc Hierarchies (Yahoo!) structured Glossaries

XML DTDs Data Dictionaries (EDI) ‘ordinary’ Glossaries XML Schema DB Schema

Glossaries & Data Dictionaries MetaData, XML Schemas, & Data Models Formal Ontologies & Inference Thesauri, Taxonomies

Formalities of Knowledge Representations

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What is an Ontology?

“a specification of a conceptualization”* Ontologies explicitly represent key concepts, their properties, their relationships, and their rules and constraints. Ontologies often focus more heavily on the meaning of concepts as opposed to terms that are used to represent them Vocabulary + Structure = T axonomy T axonomy + (Relationships and Constraints) = Ontology

*T

  • m Gruber, Stanford Univ.
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Ontology Application Scenarios

Common Access to Information

Information required by multiple agents Provides a single source of information for multiple applications Ontology used as agreed standard Benefits: knowledge reuse, maintainability, long term knowledge retention

Ontology Application 1 Application 2 Application 3 references references

OA

references

  • Ontology as Specification

–

build ontology for required domain

–

produce software consistent with ontology

–

manual or partially automated

–

Benefits: documentation, maintenance, reliability, knowledge (re)use

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Ontology Application Scenarios (cont.)

Ontology as an Exchange Language

Provides an interlingua among disparate applications Ensures semantic-based interoperability Solves the point-to-point integration problem Benefits: systems integration, semantic interoperability

  • Ontologies for Reasoning

–

Allows one to run queries through a reasoning engine

–

Helps to identify information that is not explicitly represented

–

Benefits: knowledge inference

Application Ontology

Reasonin g Engine AD OA

accesses Interfaces with

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Ontologies for Robotics and Automation

Approach

T

  • p down

Develop/identify an upper ontology to serve as the overarching structure that information can “hang from” Develop a methodology to add new information to the ontology Bottom Up Develop detailed ontologies for a small set of domains

  • Service Robots
  • Autonomous Robots

Domains are intentionally broad to allow for overlapping concepts T ying it all together Incorporate the domain ontologies into the upper ontology using the defined methodology Reconcile any discrepancies that exist among concepts

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Define a framework for building ontologies that allows robot designers to build domain-specific

  • ntologies in a controllable way

Define linguistic framework so that expressions using the ontologies can be communicated and so that it is possible to translate between different ontological realms (e.g. human and robot) Define top-level categories as a foundation for further extension

Upper Ontology and Framework Subgroup

Goals

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Service Robot Ontology Subgroup

Types of Service Robots

“A Service Robot is a robot which operates semi- or fully autonomously to perform services useful to the well- being of humans and equipment, excluding manufacturing operations” - International Federation of Robotics (IFR)

Industrial robots (e.g., radiographic inspection of welds) Defense robots (e.g., autonomous scout vehicles) Healthcare robots (e.g., surgical manipulation, wheel chairs) Prosthetic robots (e.g., prosthetic arms, legs, etc.) Scientific robots (e.g., gene sequencers) Domestic robots (e.g., floor cleaners, lawn mowers) Diffused robots (e.g., parallel park assist systems) Military and law enforcement robots (e.g., drones, UAVs)

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Service Robot Ontology Subgroup

Approach

Phase 1: Identify and summarize the different definitions and glossaries used in the different Service Robots - bibliographical research Phase 2: Requirement analysis to extend /modify the glossaries to meet the needs of industries and scientific communities Phase 3: Aims at describing the robots in terms of well- defined ‘taxonomy’ by its components and operating environment Phase 4: Defines and elaborates on the different knowledge layers - for high level Human-Robot/Robot-Robot Interaction

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Autonomous robots are robots that can perform desired tasks in unstructured environments without continuous human guidance.

aerial photography using flying robots customs and border security electricity companies, who can inspect power lines, nuclear power plants, wind turbines, and other facilities using robots gas and oil supply companies, who can use robots to inspect, maintain, and guard pipelines local civic authorities meteorological services, who can use UAVs to carry weather stations river authorities and water boards landmine detection and destruction.

Autonomous Robots Ontology Subgroup

Overview

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Description of robot hardware, software Description of the activities that need to be performed Description of the environment in which the robot needs to work Understand of cause and effect of performing actions Relationship among other robots and/or people …

Autonomous Robots Ontology Subgroup

Knowledge Representation

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Investigate standards from other SDOs (ISO, ALFUS) Investigate existing efforts and formalisms and list the advantages/disadvantages Collect practice in academia/industry (interview business management) Collect academia/industry requirements for standardizing autonomous robots ontology How to represent the terminology? Dictionaries, Glossaries, XML schemas, Databases, Logic-Based approaches, Others? Define ontology/glossary for autonomous robots Define glossaries specific to autonomous robots Define ontology for autonomous robots (air, ground, water, space) Define ontology for sub-domains, sensor, perception, fusion, actuator, control, guidance, navigation, motion planning, mission planning, decision making (or software, hardware, electrical, mechanical, performance, …) Define ontology for human machine interactions Use of ontology to *describe* autonomous robots.

Set up a long-term roadmap for autonomous robots

  • ntology

Autonomous Robots Ontology Subgroup

Approach

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PAR Procedures

PAR (Project Authorization Request) is the documentation necessary to start the process of turning a Study Group into a IEEE-Recognized Working Group September 16th - PAR drafted and submitted through IEEE Robotics and Automation Society/Standing Committee for Standards Activities (RAS-SCSA) mid-October - NesCOM (New Standards Committee) will review the PAR and make recommendations to the IEEE-SA Standards Board regarding approval. Responsible for ensuring that proposed standards projects are within the scope and purpose of IEEE, assigned to the proper Society or other organizational body, and interested parties are appropriately represented in the development of IEEE standards.

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How T

  • Get Involved

Come to our meeting tomorrow (Sept 26th)! Union Square Rooms 23&24 (4th floor), 9am-12:30pm Contact me: Email: craig.schlenoff@nist.gov Phone: 301-975-3456 Join our Google group

IEEE RAS Ontologies for Robotics and Automation https://groups.google.com/forum/#!forum/ieeeraswg

Visit the Web site set up for Autonomous Robots Group (http://aro.svn.sourceforge.net/)