The large FlexCRAFT research program, uniting five universities and 14 companies, including Marel, has been initiated to advance robotization in the agriculture and food industry. Eldert van Henten has led the FlexCRAFT project since 2019. ”In an earlier stage, people still thought it was technically too ambitious. But by 2018, great progress was made in the automotive and medical sectors in terms of algorithms, vision, sensors, deep learning and control. Based on that, we can now move forward.”
Eldert Van Henten continues, “Until recently, robots in this industry recorded the environment, deduced relevant data, planned a movement with their robotic arm and started to pick up, cut or manipulate an object. In the end, the robot didn’t know if the action had been successful. That is why FlexCRAFT adds so-called ‘active perception’ to the robot’s algorithm. Now, the robot can permanently acquire new relevant data during the action. Acquired knowledge from previous actions isn’t lost anymore, but stored in a mathematical ‘world model’. The robot becomes self-learning and knows henceforth that it shouldn’t focus on the leaves, but on the truss of tomatoes. From then on, when the same action re-occurs, the robot can retrieve the truss location information from its memory.
In addition, the researchers are drafting a library with stored actions, avoiding a constant complete recalculation for every repeated action. Taking the human hand movement as an example, the TU Delft research team generates mimicked motions for this library. The algorithm looks like a ‘human muscle memory’ that quickly retrieves the optimal way to pick up or grab an object.