Anthony Downs, William Harrison and Craig Schlenoff
This paper aims to define and describe test methods and metrics to assess industrial robot system agility in both simulation and in reality.
Abstract
Purpose
This paper aims to define and describe test methods and metrics to assess industrial robot system agility in both simulation and in reality.
Design/methodology/approach
The paper describes test methods and associated quantitative and qualitative metrics for assessing robot system efficiency and effectiveness, which can then be used for the assessment of system agility.
Findings
The paper describes how the test methods were implemented in a simulation environment and real-world environment. It also shows how the metrics are measured and assessed as they would be in a future competition.
Practical implications
The test methods described in this paper will push forward the state of the art in software agility for manufacturing robots, allowing small and medium manufacturers to better utilize robotic systems.
Originality/value
The paper fulfills the identified need for standard test methods to measure and allow for improvement in software agility for manufacturing robots.
Details
Keywords
Frederick Proctor, Stephen Balakirsky, Zeid Kootbally, Thomas Kramer, Craig Schlenoff and William Shackleford
This paper aims to describe an information model, the Canonical Robot Command Language (CRCL), which provides a high-level description of robot tasks and associated control and…
Abstract
Purpose
This paper aims to describe an information model, the Canonical Robot Command Language (CRCL), which provides a high-level description of robot tasks and associated control and status information.
Design/methodology/approach
A common representation of tasks was used that is understood by all of the resources required for the job: robots, tooling, sensors and people.
Findings
Using CRCL, a manufacturer can quickly develop robotic applications that meet customer demands for short turnaround, enable portability across a range of vendor equipment and maintain investments in application development through reuse.
Originality/value
Industrial robots can perform motion with sub-millimeter repeatability when programmed using the teach-and-playback method. While effective, this method requires significant up-front time, tying up the robot and a person during the teaching phase.
Details
Keywords
Behzad Bayat, Julita Bermejo-Alonso, Joel Carbonera, Tullio Facchinetti, Sandro Fiorini, Paulo Goncalves, Vitor A.M. Jorge, Maki Habib, Alaa Khamis, Kamilo Melo, Bao Nguyen, Joanna Isabelle Olszewska, Liam Paull, Edson Prestes, Veera Ragavan, Sajad Saeedi, Ricardo Sanz, Mae Seto, Bruce Spencer, Amirkhosro Vosughi and Howard Li
IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous…
Abstract
Purpose
IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous robotics. This paper aims to present the work in-progress developed by the autonomous robotics (AuR) subgroup. This group aims to extend the core ontology for robotics and automation to represent more specific concepts and axioms that are commonly used in autonomous robots.
Design/methodology/approach
For autonomous robots, various concepts for aerial robots, underwater robots and ground robots are described. Components of an autonomous system are defined, such as robotic platforms, actuators, sensors, control, state estimation, path planning, perception and decision-making.
Findings
AuR has identified the core concepts and domains needed to create an ontology for autonomous robots.
Practical implications
AuR targets to create a standard ontology to represent the knowledge and reasoning needed to create autonomous systems that comprise robots that can operate in the air, ground and underwater environments. The concepts in the developed ontology will endow a robot with autonomy, that is, endow robots with the ability to perform desired tasks in unstructured environments without continuous explicit human guidance.
Originality/value
Creating a standard for knowledge representation and reasoning in autonomous robotics will have a significant impact on all R&A domains, such as on the knowledge transmission among agents, including autonomous robots and humans. This tends to facilitate the communication among them and also provide reasoning capabilities involving the knowledge of all elements using the ontology. This will result in improved autonomy of autonomous systems. The autonomy will have considerable impact on how robots interact with humans. As a result, the use of robots will further benefit our society. Many tedious tasks that currently can only be performed by humans will be performed by robots, which will further improve the quality of life. To the best of the authors’knowledge, AuR is the first group that adopts a systematic approach to develop ontologies consisting of specific concepts and axioms that are commonly used in autonomous robots.
Details
Keywords
Juan Ignacio Vazquez, Diego López de Ipiña and Iñigo Sedano
Despite several efforts during the last years, the web model and semantic web technologies have not yet been successfully applied to empower Ubiquitous Computing architectures in…
Abstract
Despite several efforts during the last years, the web model and semantic web technologies have not yet been successfully applied to empower Ubiquitous Computing architectures in order to create knowledge‐rich environments populated by interconnected smart devices. In this paper we point out some problems of these previous initiatives and introduce SoaM (Smart Objects Awareness and Adaptation Model), an architecture for designing and seamlessly deploying web‐powered context‐aware semantic gadgets. Implementation and evaluation details of SoaM are also provided in order to identify future research challenges.