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International Journal of Automation and Computing 2018, Vol. 15 Issue (5) :515-524    DOI: 10.1007/s11633-018-1130-2
Special Issue on Intelligent Control and Computing in Advanced Robotics Current Issue | Next Issue | Archive | Adv Search << Previous Articles | Next Articles >>
Software for Small-scale Robotics: A Review
Tobias Tiemerding1,2, Sergej Fatikow1
1. Department of Computing Science, Division Microrobotics and Control Engineering (AMiR), University of Oldenburg, Ammerländer Heerstraße 114-118, Oldenburg D-26129, Germany;
2. OFFIS-Institute for Information Technology, R&D Division Automation and Integration Technology (AIT), Escherweg 2, Oldenburg D-26121, Germany
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Abstract In recent years, a large number of relatively advanced and often ready-to-use robotic hardware components and systems have been developed for small-scale use. As these tools are mature, there is now a shift towards advanced applications. These often require automation and demand reliability, efficiency and decisional autonomy. New software tools and algorithms for artificial intelligence (AI) and machine learning (ML) can help here. However, since there are many software-based control approaches for small-scale robotics, it is rather unclear how these can be integrated and which approach may be used as a starting point. Therefore, this paper attempts to shed light on existing approaches with their advantages and disadvantages compared to established requirements. For this purpose, a survey was conducted in the target group. The software categories presented include vendor-provided software, robotic software frameworks (RSF), scientific software and in-house developed software (IHDS). Typical representatives for each category are described in detail, including SmarAct precision tool commander, MathWorks Matlab and national instruments LabVIEW, as well as the robot operating system (ROS). The identified software categories and their representatives are rated for end user satisfaction based on functional and non-functional requirements, recommendations and learning curves. The paper concludes with a recommendation of ROS as a basis for future work.
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KeywordsRobotic control   software engineering   micro/nano robotics   artificial intelligence (AI)   machine learning (ML)   open source     
Received: 2018-01-15;
Corresponding Authors: Tobias Tiemerding     Email: tobias.tiemerding@uni-oldenburg.de
About author: Tobias Tiemerding has published 52 conference and journal papers and a book chapter. His research interests include microrobotics, automation, software-based control and high-speed image processing. E-mail: tobias.tiemerding@uni-oldenburg.de (Corresponding author) ORCID iD: 0000-0003-1800-4758;Sergej Fatikow research interests include micro/nanorobotics, industrial robotics and automation at nanoscale, nanohandling inside SEM, AFM-based nanohandling, sensor feedback at nanoscale, and robot control.E-mail: fatikow@uni-oldenburg.de
Cite this article:   
Tobias Tiemerding, Sergej Fatikow. Software for Small-scale Robotics: A Review[J]. International Journal of Automation and Computing , vol. 15, no. 5, pp. 515-524, 2018.
http://www.ijac.net/EN/10.1007/s11633-018-1130-2      或     http://www.ijac.net/EN/Y2018/V15/I5/515
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