Towards a Robot Task Ontology Standard (original) (raw)

Ontology for autonomous robotics

2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2017

Creating a standard for knowledge representation and reasoning in autonomous robotics is an urgent task if we consider recent advances in robotics as well as predictions about the insertion of robots in human daily life. Indeed, this will impact the way information is exchanged between multiple robots or between robots and humans and how they can all understand it without ambiguity. Indeed, Human Robot Interaction (HRI) represents the interaction of at least two cognition models (Human and Robot). Such interaction informs task composition, task assignment, communication, cooperation and coordination in a dynamic environment, requiring a flexible representation. Hence, this paper presents the IEEE RAS Autonomous Robotics (AuR) Study Group, which is a spin-off of the IEEE Ontologies for Robotics and Automation (ORA) Working Group, and and its ongoing work to develop the first IEEE-RAS ontology standard for autonomous robotics. In particular, this paper reports on the current version of the ontology for autonomous robotics as well as on its first implementation successfully validated for a human-robot interaction scenario, demonstrating the developed ontology's strengths which include semantic interoperability and capability to relate ontologies from different fields for knowledge sharing and interactions.

An ieee standard ontology for robotics and automation

2012

Abstract This article discusses a newly formed IEEE-RAS working group entitled Ontologies for Robotics and Automation (ORA). The goal of this working group is to develop a standard ontology and associated methodology for knowledge representation and reasoning in robotics and automation, together with the representation of concepts in an initial set of application domains.

Exploring the IEEE ontology for robotics and automation for heterogeneous agent interaction

Robotics and Computer-Integrated Manufacturing, 2015

Spatial notions play a key role when humans and robots interact. Robotics & Automation (R&A) often involves diverse scenarios where heterogeneous robots must share their spatial knowledge to achieve a given goal. Such scenarios may become more complex when humans are also involved. This means that humans and heterogeneous robots must share their spatial information about the world. For this purpose, the IEEE Ontologies for Robotics and Automation (ORA) Working Group started developing an ontology, called POS, with the purpose of defining the core notions required to share spatial concepts in the R&A domain. This paper evaluates the proposed ontology through a use case scenario involving both heterogeneous robots and human-robot interactions, showing how to define new spatial notions using POS. We discuss the experiment results presenting the ontology strengths as well as the future directions to be taken by the ORA group.

Ontology-Based Knowledge Representation in Robotic Systems: A Survey Oriented toward Applications

Applied Sciences, 2021

Knowledge representation in autonomous robots with social roles has steadily gained importance through their supportive task assistance in domestic, hospital, and industrial activities. For active assistance, these robots must process semantic knowledge to perform the task more efficiently. In this context, ontology-based knowledge representation and reasoning (KR & R) techniques appear as a powerful tool and provide sophisticated domain knowledge for processing complex robotic tasks in a real-world environment. In this article, we surveyed ontology-based semantic representation unified into the current state of robotic knowledge base systems, with our aim being three-fold: (i) to present the recent developments in ontology-based knowledge representation systems that have led to the effective solutions of real-world robotic applications; (ii) to review the selected knowledge-based systems in seven dimensions: application, idea, development tools, architecture, ontology scope, reason...

Extensions to the core ontology for robotics and automation

Robotics and Computer-Integrated Manufacturing, 2015

The working group Ontologies for Robotics and Automation, sponsored by the IEEE Robotics & Automation Society, recently proposed a Core Ontology for Robotics and Automation (CORA). This ontology was developed to provide an unambiguous definition of core notions of robotics and related topics. It is based on SUMO, a top-level ontology of general concepts, and on ISO 8373:2012 standard, developed by the ISO/TC184/SC2 Working Group, which defines-in natural language-important terms in the domain of Robotics and Automation (R&A). In this paper, we introduce a set of ontologies that complement CORA with notions such as industrial design and positioning. We also introduce updates to CORA in order to provide more ontologically sound representations of autonomy and of robot parts.

A Robotic and Automation Services Ontology

The complexity and diversity of our homes call for creative and integrated solutions to make it smarter. We aim to discuss some problems in heterogeneous agent cooperation and generic action composition mechanism in this field. This involve to build a brand new information system to target the issue with an adapted architecture and a coherent models. The composition of usage scenarios could become a real issue since the agents are heterogeneous in nature (human, robot, connected objects), share different properties (probe/actuator, predictable/unpredictable) and use different type of communications. The current contribution is a part of a global project ASTRO which is an architecture providing communication gateway, unified interaction interfaces and information exchange. In order to facilitate the scenario composition we use and integrate ontologies in this framework to create a simple and efficient concept map of the field. This work also created a high level action composition mo...

A flexible task knowledge representation for service robots

The 9th International …, 2006

Robots that are designed to act in human-centered environments put up the need for a flexible and adaptive representation of task knowledge. This results on the one hand from the continuously changing and hardly predictable state of an environment that is populated with humans and robots. On the other hand, a task knowledge description of a robot which cooperates with humans has to be adaptable and extendable. This paper presents a task knowledge representation for service robots called Flexible Programs (FP) and the environment for execution of FPs. Flexible Programs can be created manually, or by using the results of machine learning approaches like Programming by Demonstration. It is possible to change, adapt and extend this task knowledge at runtime.

A Robot Ontology for Urban Search and Rescue | NIST

conference on information and knowledge management, 2006

The goal of this Robot Ontology effort is to develop and begin to populate a neutral knowledge representation (the data structures) capturing relevant information about robots and their capabilities to assist in the development, testing, and certification of effective technologies for sensing, mobility, navigation, planning, integration and operator interaction within search and rescue robot systems. This knowledge representation must be flexible enough to adapt as the robot requirements evolve. As such, we have chosen to use an ontological approach to representing these requirements. This paper describes the Robot Ontology, how it fits in to the overall Urban Search and Rescue effort, how we will be proceeding in the future.

Towards an Ontology for Autonomous Robots," in

2012

Abstract-The IEEE RAS Ontologies for Robotics and Automation Working Group is dedicated to developing a methodology for knowledge representation and reasoning in robotics and automation. As part of this working group, the Autonomous Robots sub-group is tasked with developing ontology modules for autonomous robots. This paper describes the work in progress on the development of ontologies for autonomous systems. For autonomous systems, the focus is on the cooperation, coordination, and communication of multiple unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and autonomous underwater vehicles (AUVs). The ontologies serve as a framework for working out concepts of employment with multiple vehicles for a variety of operational scenarios with emphasis on collaborative and cooperative missions.