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 Smar Act precision tool commander, Math Works Matlab and national instruments Lab VIEW, 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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