Software for Small-scale Robotics: A Review


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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Corresponding author

Correspondence to Tobias Tiemerding.

Additional information

Recommended by Guest Editor Jun-Zhi Yu

Tobias Tiemerding received the B. Sc. and M. Sc. degrees in computer science and embedded systems and microrobotics from University of Oldenburg, Germany in 2010 and 2012, respectively. Currently, he is a research associate in Department of Computing Science, Division Microrobotics and Control Engineering (AMiR), University of Oldenburg, Germany. He has published 52 conference and journal papers and a book chapter.

His research interests include microrobotics, automation, soft-ware-based control and high-speed image processing.

Sergej Fatikow received the Ph. D. degree in computer science and electrical engineering at Ufa Aviation Technical University, Russia in 1988. He is a full professor in Department of Computing Science and head of the Division Microrobotics and Control Engineering (AMiR) at University of Oldenburg, Germany. He has published about 150 book chapters and journal papers and about 300 conference papers. He is a Member of IEEE, founding chair of the International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), founding chair of the International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) and Europe-chair of IEEE-RAS Technical Committee on Micro/Nano Robotics and Automation.

His research interests include micro/nanorobotics, industrial robotics and automation at nanoscale, nanohandling inside SEM, AFM-based nanohandling, sensor feedback at nanoscale, and robot control.

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Tiemerding, T., Fatikow, S. Software for Small-scale Robotics: A Review. Int. J. Autom. Comput. 15, 515–524 (2018).

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  • Robotic control
  • software engineering
  • micro/nano robotics
  • artificial intelligence (AI)
  • machine learning (ML)
  • open source.