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Coding the Future: A time travel through robot programming

Coding the Future: A time travel through robot programming

Colette White

July 1, 2024

Coding the Future: A time travel through robot programming

Welcome to our new series: "Coding the Future," where we explore the technologies shaping tomorrow's world. Before we look to the future, it's always fun to walk through the past and learn about why we program robots today the way we do. 

 

The History of Industrial Robot Programming


Robot programming has come a long way since the development of the first programming language. It was developed by German native Konrad Zuse and was called “Plankalkül”. We will skip the deep dive as it was for computers, not robots. However, this first programming language marked an important milestone on the way of the first robot programming language. The last one is called "MHI" and is considered the first robot language, developed to control a robot arm in 1960 at MIT. It took a decade for general purpose robot programming languages to come onto the scene and rise to popularity.


Konrad Zuse, Plankalkül - Source: IEEE, Facebook Post (October 19, 2017)

 

As industrial robots evolved and began to be led by the powerhouse brands that are so well-known today, programming languages became more proprietary. Each brand has its own language, such as RAPID for ABB, KRL for KUKA, and Yaskawa's Inform II. Each of these languages allows for more sophistication when programming robots. They are tailored to the specific robot brand capabilities, which offers more precision and control over programming.

 

One of the earliest tools for industrial robot programming was the teach pendant, a handheld device used to manually guide a robot and record its positions sequentially. Early renditions of the teach pendant were rudimentary by today's standards. While robot programming and even teach pendants have evolved a lot since their introduction, they are still standard robot programming tools. Even with the newest model of teach pendants, this tool needs more flexibility and scalability to program more complex robot tasks.

 

 

Challenges of Traditional Industrial Robot Programming

 

With all great technology, there are pros and cons. Below are some of the challenges experienced with traditional robot programming.

 

  • Complexity and Precision: Branded robot languages are designed to harness each feature of their respective robots to its full potential, which has a steep learning curve. Programmers must know each language's syntax and structure and the intricacies of mechanical and electrical robot systems. This type of detailed programming leads to even minor tasks becoming time-consuming.

  • Comprehensive Coding Knowledge: Coding knowledge is paramount for the fluency of traditional robot programming. Unlike general-purpose programming languages (think Python or JavaScript), robot-specific languages are not taught everywhere. This makes entering the robot programming field more difficult, limiting the talent pool of qualified people proficient in programming and operating industrial robots.

  • Trademarked Languages: As mentioned previously, each major robot OEM has developed a distinct programming language. This adds to the field's silos and increases complexity. Programmers skilled in one language usually stay with the type of robot they know; they don’t branch out. The lack of a standard programming language means continuously learning and adapting, and it blocks programmers from seamlessly programming different brands of robots.

  • Time and Price: Traditionally, robot programming is a time-consuming and expensive skill. As not many people have the know how to program robots, skilled programmers demand a lot of money for their expertise. Aside from their great expertise, programming is a time-consuming task as debugging and optimization takes a lot of time, especially when unidentified issues come to light from the robot's environment. Testing and bug fixes are a constant back and forth between code and running the robot. Another downside of traditional robot programming is robot downtime, meaning the robot has to be off to adjust the code. There is no simulation with traditional robot programming to make debugging faster.

 

Modern Robotics

 

The challenges of traditional robot programming have gotten to the point where companies like Wandelbots are disrupting the industry to make space for solutions that are intuitive and more accessible for robot programming from initial planning to final stage operations.

These new solutions reduce complexity and lower the barrier to entry, growing a more inclusive and versatile robot ecosystem.

 

  • Graphical User Interfaces (GUIs) program robots by using visuals over text code for a more intuitive user experience. These interfaces have drag-and-drop functions and flowchart-based programming, simplifying the process and allowing users with limited coding backgrounds to program robots effectively. However, they also have challenges, as you are limited to the functions provided and must fit them to your scenario. There is no option to create your own.

  • Simulation environments with a digital twin of exact replicas of physical robots allow programmers to visualize and test robot programs better in a virtual space before deployment. A simulation environment saves time and resources by running robot programs multiple times to reduce effort while identifying potential problems in the program logic or robot movement, drastically reducing robot downtime.

  • Artificial Intelligence (AI) and Machine Learning (ML) allow for adaptive and robot self-learning when integrated into robot programming. With AI and Machine Learning, robots can learn tasks to improve performance through iterative learning processes, making detailed manual programming less essential.

  • Unified programming languages have come a long way in standardizing programming languages for robots and allowing cross-platform programming. Tools like robotic platform libraries provide unified frameworks to support various robot models and brands. This eases the learning curve and promotes interoperability between OEMs.

  • Low-code and no-code robot programming has become instrumental in bringing a new level of accessibility to robot programming. Some of these interfaces rely on visual and pre-built modules to create complex programs using little to no programming knowledge. Pre-coded building blocks let users move robots without lines of complicated code, speeding up programming time and opening doors for those without technical experience.

 

Robot Simulation Environment with digital Twin
Simulation Environment with digital Twin. Source: Wandelbots

Simple Robot Programming with Wandelbots

 

Wandelbots was founded on the belief that human-robot interactions don't have to be complicated. Our robotic software platform integrates with multiple peripherals, tools, and robots to simplify robot programming. The following core benefits contribute to our success:

 

  • Intuitive Software Platform: Our customer centric software for programming and building robot programs is the backbone of our holistic solution, putting the user at the center of the robot lifecycle. Users of our platform can build their own robot programs to adjust parameters, optimize paths, and build and deploy programs with limited technical experience all on one platform.

  • User-Friendly Interface: Our software prioritizes user-friendliness, placing the user at the heart of our product. We focus on easy human-robot interaction, similar to the intuitive interaction with any website builder today. With our Python-based code, anyone with a basic knowledge of Python can program robots intuitively and easily, all thanks to an amazingly simplified interface.

  • Hardware Agnostic: With one platform, hardware integration is easy. Integrations for grippers, sensors, robots, and any other periphery can be added to the software platform, making building robotic programs more effortless and accessible.

  • Flexibility and Adaptability: The Wandelbots’ robotic software platform caters to multiple industrial applications, allowing you to build and deploy between welding, painting, sanding, and, more importantly, the specific use cases you experience on the shop floor. The flexible nature of our platform makes it an attractive solution for those ready to enhance their automation with less cost and complexity than traditional robot programming. The adaptability to plan a robot cell, from start to finish, using our basic simulation software or integrating with our Nvidia Omniverse plugin for a more robust experience lowers potential risk.

  • Cost and Time Efficiency: As mentioned above, modern robot programming saves time and money when programming robots. Companies can program, deploy, and reprogram their robots quickly while responding to changes in production with agility and efficiency. Using our robot app builder, they can also use in-house resources to adjust automation, giving them more control.

 

Conclusion

Industrial robot programming has come a long way from the original teach pendants. This evolution to more intuitive and user-friendly AI-driven programming methods shows an industry opening doors and making robots and automation more accessible.

 As we continue to make the robot programming barriers disappear, we can look forward to higher robot adoption and automation that copies the technology we use daily.

Are you interested in learning more about Wandelbots' robotic software platform? Let's talk! Connect with us and learn how to start your automation and robot programming journey. Look for more insights as we continue to explore robot programming in our "Coding the Future" series.

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