Mokaram, S, Aitken, JM, Martinez-Hernandez, U orcid.org/0000-0002-9922-7912 et al. (6 more authors) (2017) A ROS-integrated API for the KUKA LBR iiwa collaborative robot. In: IFAC-PapersOnline. 20th IFAC World Congress, 09-14 Jul 2017, Toulouse, France. Elsevier , pp. 15859-15864.
Abstract
The deployment of collaborative robotic systems in industry 4.0 raises the potential for complex human-robot interaction to create highly flexible processes. This brings a need for systems that can facilitate rapid programming and development of safe collaborative processes, without the need for extensive training. In this paper we introduce a novel Application Programming Interface (API) for the KUKA Intelligent Industrial Work Assistant (iiwa) Lightweight Robot (LBR) that enables fast development and integration of devices, using the popular Robot Operating System (ROS), without compromising the inherent safety features of the robot. We describe the API, released as a freely available download, and provide an example application of its use to support a large-scale interactive participant experiment. As flexible manufacturing technologies become ever more connected and complex, it is important to ensure compatibility between networked devices and provide tools to support system integration based on common platforms. Our API is one such tool, and has been designed to support faster and easier system integration and development, providing particular support to scientists in creating experiments for studying human-robot collaboration.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Keywords: | Programming; Collaborative Robotics; Industrial Robot; Flexible Manufacturing |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Mar 2018 16:16 |
Last Modified: | 20 Mar 2018 13:45 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.ifacol.2017.08.2331 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:128650 |