The Project
Robots are among the most flexible machine tools available today for industrial use. While conventional machine tools are usually highly specialised designs for individual application scenarios, industrial robots (with the right tool) can be used for an extremely wide range of operational scenarios. As a consequence, one would expect specialised machine tools to be used primarily in large-scale production and industrial robots, because of their flexibility, to be used more in the production of prototypes and very small series. However, industrial practice shows exactly the opposite: industrial robots are used today almost exclusively in large series. They play practically no role in prototyping and small batch production.
Surprisingly, the decisive reason for this lies in the programming of the robot. Although this is conceptually very simple - it is often only a single sequence of movements that has to be iteratively repeated - programming for a concrete application scenario involves extremely high costs. These often exceed the acquisition costs and are in principle incurred again every time the task is changed. A whole series of current research and transfer projects are addressing this problem.
Figure. 1: Path planning tasks. The effective tasks A to F must be connected by support tasks
Two fundamentally different approaches can be observed. On the one hand, attempts are made to improve or replace programming through the principle of "teaching". The great advantage of teaching-based methods lies in their ease of application. However, the robot will only imitate the movements of humans, which are usually imprecise and rarely time- or energy-efficient. As a result, only a fraction of the potential of automation is exploited. In parallel, a second group of approaches is trying to make (manual) programming more (time-) efficient. This includes new, modular software architectures, the standardisation of programming languages and environments, and the introduction of generic frameworks. This makes it possible to programme robots more time-efficiently.
In this project, the innovation potential of a third, complementary approach is to be validated. Instead of creating programme sequences manually, these are automatically derived from a model of the product to be manufactured and the machining process. Existing approaches focus on the - relatively simple - part of generating robot paths from given CAD data. The main problem, however, lies in the calculation of optimal, collision-free infeed movements and work sequences. In purely conceptual terms, this leads to the problems of programme and controller synthesis.
Figure. 2: Presentation of possible innovation potentials
Both problems cannot be solved completely generically. However, there are very efficient solutions for outstanding subproblems. In the context of industrial robotics, this means generating sequences of trajectories that satisfy a number of constraints, such as freedom from collision, energy optimality and minimum processing time. For this restricted class of problems, the applicants were able to design very efficient methods. If these methods can be efficiently connected to standard industrial robots, a leap innovation can be achieved. By automating a large part of the integration tasks, the cost of adapting a robot to changing tasks can be reduced by up to 90% (We see a 90% reduction as achievable for simple applications such as assembly/soldering. For more complex problems, we expect a reduction of up to 50%.), which would open up a range of new application scenarios for industrial robotics. This leads to innovation and sales growth for both end users and robot manufacturers.
Figure. 3: Currently, tasks B to E have to be carried out manually by an operator with sufficient
expertise. These tasks are to be automated for the most part thanks to VIP+-AuRora.
In summary: The aim of this project is to validate the innovation potential of model-based techniques for automatically generating efficient control programmes for industrial robots.
If successful, a leap innovation will result from the higher degree of automation in domains where small batches are produced. It will be part of the project to decide whether the targeted innovation can be most promisingly exploited economically as a service, product or combination of both.
