Programming Languages for Industrial Robots

1986 ◽  
Author(s):  
Christian Blume ◽  
Wilfried Jakob
Keyword(s):  
Programming Languages ◽  
Industrial Robots

Explicit programming languages in industrial robots

1983 ◽  
Vol 2 (1) ◽  
pp. 53-60 ◽  
Author(s):  
Giuseppina Gini ◽  
Maria Gini
Keyword(s):  
Programming Languages ◽  
Industrial Robots

Introducing Intuitive and Versatile Multi Modal Graphical Programming Means to Enhance Virtual Environments

2008 ◽  
Author(s):  
Ju¨rgen Roßmann ◽  
Michael Schluse ◽  
Thomas Jung
Keyword(s):  
Programming Languages ◽  
Virtual Environments ◽  
Programming Language ◽  
Industrial Robots ◽  
3D Simulation ◽  
Modeling Languages ◽  
Graphical Modeling ◽  
Graphical Programming ◽  
Dynamic Components ◽  
Simulation Systems

Usability and versatility are two of the most important issues when using modern 3D simulation systems within the field of automation technology and virtual environments. 3D simulations and virtual worlds proved to be versatile tools to program, supervise and command complex robotic and automation systems. For industrial robots, 3D simulation systems like COSIMIR® introduced the so called Native Language Programming (NLP) concept enabling the automation expert to program each robot using its native programming language. But what about programming other automation components or other dynamic components in virtual environments, what about user friendly, intuitive graphical programming languages, what about easy-to-use worker oriented programming languages? When talking about graphical programming languages to model dynamic behavior, questions like “which graphical modeling languages should be supported?”, “which are the most powerful ones?” and “which one matches the most to my concrete application?” have to be answered. Each graphical programming language has its own advantages and disadvantages, so that the answer to all these questions has to be: Offer a choice of graphical modeling languages to the user and leave the decision to him. The advantage of this strategy is obvious: Instead of learning how to use a concrete modeling language or worrying about programming details, the user can focus on his individual automation task and so quickly build efficient solutions. Therefore this paper extends the NLP approach to graphical programming languages using a new kind of object oriented Petri Nets as an intermediate language. This enables the user to use — at the same time — finite automata like mealy machines or extended automata, activity diagrams as defined in UML 2, flowchart like diagrams (e. g. icon-based programming) and many more to model the dynamics or the behavior of dynamic components.

Automated planning and programming environments for robots

Robotica ◽  
1992 ◽  
Vol 10 (1) ◽  
pp. 75-82 ◽  
Author(s):  
H. A. ElMaraghy ◽  
J. M. Rondeau
Keyword(s):  
Programming Languages ◽  
Industrial Robots ◽  
Robot Programming ◽  
Programming System ◽  
Levels Of Abstraction ◽  
Natural Manner ◽  
Programming Environments ◽  
The Individual ◽  
Time Required ◽  
Task Level

SummaryTraditionally, most industrial robots are programmed by teaching. Automatic planning of robotic tasks has many potential benefits for flexible automation. It allows the user to describe a task to the robot programming system in a formal and natural manner, and reduces the time required to generate and update robot programs. Two main levels of abstraction in describing robot tasks can be identified. Robot-level programming is based on robot movements and actions, as detailed by the programmer. Object-level or task-level programming allows the user to describe assembly tasks in terms of operations performed on objects being manipulated instead of specifying the individual motions of the robot end-effector. However, commercially available robot-level programming languages still fall short of the robot user's need to programme complex tasks and consequently are not widely used in industry. There is an increasing need for integrating sensors feedback into the robot system to provide better perception and for improving the capacity of the robot to reason and make decisions intelligently in real-time. Task-level programming represents the highest level of abstraction and is the most attractive, as it uses reasoning capabilities provided by Artificial Intelligence. To date, no system of this class has been completely implemented in industry. This paper reviews the progress made in robot programming and task planning systems in the last twenty years, and discusses the current research trends.

SAM-I: A prototype machine for dynamic, array-oriented programming languages

1992 ◽  
Vol 139 (4) ◽  
pp. 335
Author(s):  
R.F. Hobson ◽  
J.D. Hoskin ◽  
J.L. Simmons ◽  
R.W. Spilsbury
Keyword(s):  
Programming Languages ◽  
Dynamic Array

INFORMATION STRUCTURING FOR SOLVING TASKS IN SPREADSHEET ENVIRONMENT

2019 ◽  
pp. 42-46
Author(s):  
A. A. Nedbaylov
Keyword(s):  
Programming Languages ◽  
Engineering Students ◽  
Electronic Information ◽  
User Friendliness ◽  
Software Environment ◽  
C Programming ◽  
Source Data ◽  
Training Courses ◽  
Engineering Psychology ◽  
Different Levels

The calculations required in project activities for engineering students are commonly performed in electronic spreadsheets. Practice has shown that utilizing those calculations could prove to be quite difficult for students of other fields. One of the causes for such situation (as well as partly for problems observed during Java and C programming languages courses) lies in the lack of a streamlined distribution structure for both the source data and the end results. A solution could be found in utilizing a shared approach for information structuring in spreadsheet and software environment, called “the Book Method”, which takes into account the engineering psychology issues regarding the user friendliness of working with electronic information. This method can be applied at different levels in academic institutions and at teacher training courses.

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