Together, digital twins and Offline programming (OLP) software enable manufacturers and integrators to move more of the deployment work away from the shop floor and into a safer, faster, and more flexible virtual space.
Key Features to Consider in Digital Twin and OLP Software
Q&A with Albert Nubiola, CEO | RoboDK
What is digital twin software and how does it relate to offline programming?
Digital twin software like RoboDK creates a virtual version of a real robotic cell. That can include the robot, end-of-arm tooling, fixtures, conveyors, sensors, parts, surrounding equipment, and sometimes the wider production environment.
The value of digital twins comes from being able to test how an automation system will behave before it’s installed on the shop floor. Can the robot reach the part? Is the reference position correctly set? Are there collision risks? Is the cycle time realistic? Will the tooling work with the part geometry? These are questions that are much easier and less expensive to answer in simulation than after the equipment has been purchased and installed.
RoboDK enables highly-realistic simulations of your robot’s workspace. Credit: RoboDK
Offline programming (OLP) is closely connected. OLP software like RoboDK automatically creates robot code away from the production robot. This means production does not have to be stopped while the program is being developed or modified. OLP software eliminates complex and time-consuming pendant programming.
If the digital twin is the environment where the cell is modeled and tested, then think of OLP as the process of creating and validating the robot program.
Together, digital twins and OLP software enable manufacturers and integrators to move more of the deployment work away from the shop floor and into a safer, faster, and more flexible virtual space.
Many robot projects lose time during programming, testing, and commissioning. A good digital twin and OLP workflow reduces that uncertainty by allowing teams to explore, simulate, and refine the application before the physical cell is fully built.
What are key features to look for in digital twin and OLP software?
The first feature to look for is accurate robot simulation. The software should be able to represent the robot, the tooling, the part, and the surrounding equipment in a way that is useful for engineering decisions. It should help users check reachability, joint limits, singularities, collisions, and cycle time.
RoboDK’s calibration features provide accuracy up to 0.200 mm, enabling more accurate simulations and improved robot performance. Credit: RoboDK
Robot calibration is also extremely important. A simulation is only useful if it corresponds closely enough to the real cell. Calibration helps improve the match between the virtual model and the physical robot, which is especially important for applications where accuracy matters.
Meanwhile, offline programming capabilities enable you to get from simulation to real-world, executable robot code at the click of a button. Digital models are useful for many reasons, but they become much more valuable when users can generate real robot programs with it.
Another important feature is flexibility. Many manufacturers do not know at the beginning of a project which robot brand or model will be the best fit. They may want to compare payload, reach, cost, footprint, accuracy, or availability. If the software is tied too closely to one robot ecosystem, it can force vendor lock-in and limit your exploration, so look for digital twin software with a large library of robots and other equipment.
CAD/CAM integration is also very important, especially for applications such as machining, cutting, trimming, welding, dispensing, and additive manufacturing. Manufacturing teams already work with CAD and CAM data, so it makes sense for robotic programming to connect with those workflows instead of forcing users to start again from scratch.
Finally, I would say usability is also critical, especially for people new to automation. Some digital manufacturing tools are extremely powerful, but they can be difficult for smaller manufacturers or first-time robot users to adopt. Good software should not require every user to become a robot programming specialist before they can begin testing ideas.
The software also needs to be affordable enough that manufacturers can use it during the exploration phase, not only after they have already committed to a large automation project. In fact, many of our customers started by downloading a free trial of RoboDK to explore ideas, using our software as a platform for experimentation and testing before going on to purchase automation and a full RoboDK license.
Why does access to a large robot library matter when planning, simulating, or programming an automation project?
Robot selection is one of the first practical decisions in any automation project.
There are so many robot brands, payloads, reaches, configurations, and price points to choose from that it can be difficult knowing where to start. In some applications, several robots may appear suitable at first glance. But once you simulate the task, you may find that one model cannot reach a difficult position, another creates a collision risk, and another is larger than necessary for the job.
NASA used RoboDK software for an airplane inspection task. Credit: RoboDK
Being able to test different robots in the same virtual cell helps users make better decisions early. It can also help avoid overspecification. If a smaller robot can do the task safely and reliably, there may be no reason to buy a larger or more expensive model.
The library should not stop at robot arms. End effectors, external axes, positioners, conveyors, fixtures, and other peripherals can all affect whether the cell works in practice. A robot application is a system, not just an arm.
A large library is especially useful for integrators because they often need to compare options quickly and present a clear concept to their customers. It is also useful for manufacturers because it gives them a better understanding of what is possible before they commit to a specific hardware path.
In RoboDK, we have put a lot of effort into supporting a wide range of robot brands (>80) and models (>1,400) because we believe robot programming should be as open and flexible as possible. The automation project should determine the robot choice, not the other way around.
Is digital twin and OLP software suitable for people with no prior robotics experience?
RoboDK software has supported successful automation deployments by first-time automation users, experts at NASA, school students, and university robotics researchers.
RoboDK is suitable for people with all levels of robotics experience, from first-timers to NASA experts. Credit: RoboDK
Digital twin and OLP software definitely makes robotics more accessible to first-time automation users. RoboDK comes with example cell layouts and configurations built-in to provide a starting point for your exploration, supported by free, online training resources.
People new to robotics can use digital twin software to learn very quickly. They can import a robot, add tooling, bring in a CAD model, test reach, move the robot around, and begin to understand how the cell might work. This is much easier than learning only through a physical robot on the shop floor, where mistakes can be costly or unsafe.
Students as young as seven years old exploring industry-grade robotics, AI, and automation concepts as part of a groundbreaking collaboration between RoboDK and Pune-based SimuSoft. Credit: RoboDK
For first-time automation buyers, this is valuable even if they do not plan to program the final cell themselves. They can use the software to explore layouts, compare robot options, and identify questions to ask an integrator. That makes them a more informed buyer.
For example, a manufacturer considering a machine tending application might use a digital twin to test where the robot should be placed, whether it can reach the CNC machine, how the gripper interacts with the part, and where operators need access. Even if an integrator later completes the final design, the manufacturer has already moved beyond a vague idea.
RoboDK digital twin software enables rapid testing of different equipment and cell layouts via an intuitive interface. Credit: RoboDK
At the same time, robotics still involves safety, tooling, fixturing, process knowledge, and integration work. Digital twin and OLP software should be seen as a way to lower the barrier to entry, improve decision-making, and reduce deployment times, not as a replacement for good engineering.
What is RoboDK CAM and what impact can it have on robotic machining deployments?
Robots offer a large workspace and flexibility compared with traditional CNC machines but programming them can be complex. RoboDK CAM extends RoboDK’s capabilities with dedicated tools designed to make robotic machining faster and easier to deploy.
Typical machining applications such as milling, drilling, deburring, trimming, cutting, and additive manufacturing often start from CAD or CAM data, but translating that data into accurate, collision-free robot motion can require a lot of complex, specialist work.
RoboDK CAM reduces that complexity. It allows users to generate toolpaths, simulate the machining process, check for collisions, and produce robot programs from CAD workflows. The goal is to help users move from design to robot motion more quickly and with less manual programming.
RoboDK CAM slashes robotic machining deployment times by up to 40% Credit: RoboDK
We showcased RoboDK CAM at Automate 2026 (Booth #4476), in a compact industrial setup using a Mecademic robot. The demonstration highlighted CAD-to-robot machining, where toolpaths are generated from a CAD model and executed as a robotic machining process.
Robotic machining should not require every manufacturer to build a custom programming workflow from the ground up. If toolpath generation, simulation, collision checking, and robot code generation can happen in a more integrated environment, deployment becomes faster and more repeatable.
For manufacturers, that means less downtime, fewer manual programming steps, and faster iteration. For integrators, it can reduce engineering effort and make it easier to validate applications before committing to the final setup.
Is cost a major factor when it comes to digital twin and OLP software?
Cost is always a factor, especially for small and medium-sized manufacturers. But it is important to look at cost in the context of the whole automation project, including the affordability and ease of adoption of the digital twin and OLP software itself.
For example, some digital manufacturing and simulation platforms are extremely powerful, but they can also be costly, complex, and come with a steep learning curve. That can be a barrier for smaller manufacturers, especially when they are still exploring whether automation is the right investment. At this stage, the software needs to be practical enough to use early, not only after a major automation project has already been approved.
More broadly, the cost of software is usually small compared with the cost of a failed or delayed robot deployment. If a company buys the wrong robot, underestimates the floor space required, discovers a collision problem late, or spends weeks programming on the shop floor, those costs can quickly become much larger than the software license.
Digital twin and OLP software helps reduce those risks. It allows teams to test ideas earlier, compare options, and identify problems before the physical installation. Even if a project still requires an integrator, the buyer can enter those discussions with better information.
There is also the cost of production downtime. If programming has to be done directly on the robot, then the robot may not be producing while the robot coding is done. Offline programming reduces that dependency by allowing much of the work to happen away from the production cell.
So, the important question is “How much uncertainty, downtime, rework, and engineering effort can digital twin and OLP software remove from my automation projects?” That’s where digital twins and OLP deliver the most value.
Albert Nubiola is the founder and CEO of RoboDK, a leading software provider for industrial robot simulation and offline programming. With a deep technical background in robotic calibration and kinematics, Nubiola founded RoboDK in 2015 as a spin-off from the CoRo laboratory at École de Technologie Supérieure (ÉTS).
Since then, the RoboDK platform has grown to support over 1,400 robot arms from 80 different manufacturers, making high-level automation accessible to businesses of all sizes. Nubiola is a frequent contributor to the robotics community, focusing on the intersection of software flexibility and manufacturing efficiency.
The content & opinions in this article are the author’s and do not necessarily represent the views of RoboticsTomorrow
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