=================================================================================

Generic (or generalized) robot programming (GRP) refers to a programming system’s support for writing a robot program in one programming language or model. Therefore, the means are enabled for converting the program into vendor-specific program instructions or commands [1–3]. The "program instructions or commands" means both source code, which needs to be compiled or interpreted before runtime, and instructions or messages, which are interpreted by a target robot system or middleware at runtime. The concept of GRP stands at the basis of the so-called skill-oriented robot programming approach [2], which proposes a layered architecture, in which “specific skills” (i.e., task-level automated handling functions, such as pick and place) are created on top of so-called "generic skills" (i.e., generic robot behaviors like motions), which interface the robot-independent specific skills with robot-dependent machine controllers and sensor drivers [2]. GRP often uses code generation for interfacing different robotic systems with robot-independent path planning, computational geometry, and optimization algorithms into a layered architecture providing a "generation layer" with open interfaces [3]. Various commercial and open source GRP tools (e.g., the Robot Operating System (ROS) [4], RoboDK [5], Siemens’ Simatic Robot Integration [6], “Drag&Bot” [7], RAZER [8], etc.) are commonly used in the industrial domain, but require the development of robot drivers or code generators for each of the supported robots. Novel approachs to GRP can leverages graphical user interface (GUI) automation tools and techniques.

         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
[1] Biggs, G.; MacDonald, B. A survey of robot programming systems. In Proceedings of the Australasian Conference on Robotics and Automation, Brisbane, Australia, 10 December 2003.
[2] Archibald, C.; Petriu, E. Skills-oriented robot programming. In Proceedings of the International Conference on Intelligent Autonomous Systems IAS-3, Pittsburgh, PA, USA, 15–18 February 1993; pp. 104–115.
[3] Freund, E.; Luedemann-Ravit, B. A system to automate the generation of program variants for industrial robot applications. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Institute of Electrical and Electronics Engineers (IEEE), New York, NY, USA, 30 September–4 October 2002; Volume 2, pp. 1856–1861.
[4] Quigley, M.; Conley, K.; Gerkey, B.; Faust, J.; Foote, T.; Leibs, J.; Ng, A.Y. ROS: An open-source Robot Operating System. In Proceedings of the ICRA Workshop on Open Source Software, Kobe, Japan, 25 January 2009; Volume 3, p. 5.
[5] RoboDK. Available online: https://robodk.com/ (accessed on 25 November 2020).
[6] Siemens Simatic Robot Integration. Available online: https://new.siemens.com/global/en/products/automation/industry-software/automation-software/tia-portal/highlights/robot-integration.html (accessed on 25 November 2020).
[7] Drag&Bot. Available online: https://www.dragandbot.com/ (accessed on 25 November 2020).
[8] Steinmetz, F.; Wollschlager, A.; Weitschat, R. RAZER—A HRI for Visual Task-Level Programming and Intuitive Skill Parameterization. IEEE Robot. Autom. Lett. 2018, 3, 1362–1369.