Our focus is the automation of processes involving easily deformable materials, such as textiles or foils. A range of robotics- and AI-based solutions for the handling of solid, shape-retaining raw materials such as metals already exist to support processes in the producing and processing industries. However, the automation of processes during which easily deformable materials are processed still poses enormous challenges for computers and image processing programs, because the demands on required computing resources are often too high. Consequently, simple tasks for humans such as gripping a towel or a piece of clothing are inadequately performed by currently available robots and gripping systems.

The complexity of our use cases demands advanced robotic solutions that exceed the state of the art. sewts’ robotics team develops these technologies in-house. Our core competencies include motion and trajectory planning, real-time control of various industrial robots as well as multi-robot coordination. Furthermore, we are experts in designing reliable processes in which easily deformable materials are handled. These processes need to be tailored to the demanding material characteristics whilst being feasible to execute with robots. We use off-the-shelf industrial robots coming from different brands and combine them with our software and process knowledge. The sewts robotic brain-in-a-box equips those robots with almost human-like cognition intelligence and enables them to cope with deformable materials.

Visual information is the most important input for our robotic brain and therefore it is crucial to always provide high quality data. Depending on the use case we apply state of the art 2D or 3D vision systems – both seamlessly integrated in our systems. We are experts in enhancing the generated data which is especially relevant when working with 3D point clouds. This preprocessing is a vital building block of our systems in terms of generating usable input for our artificial intelligence.

Our AI is where the real magic happens. Smart algorithms are needed to build adaptive systems that cope with non-deterministic automation processes. That’s why we leverage the latest AI research findings, refine them for our needs and finally put them together in one big piece – our robotic brain. It receives diverse sensor data (e.g. optical information), draws conclusions on a human-like level of cognition and translates these into high-level robotic commands. That’s how our systems complete tasks that until now required human intellect.

The majority of our use cases deal with flexible materials, textiles and alike. It is essential to understand the characteristics of these materials in order to implement robust processes. We achieve that through highly sophisticated material simulations. We develop specialized FE simulations to reproduce the behavior of textiles. These simulations open up completely new possibilities in the development of smart algorithms. We use these simulations to generate synthetic training data for our AI engineering to name just one example – leading to dramatically shortening our development cycles.