»Self-learning Dynamic Locomotion Mobile Robot«
Robots have long been indispensable in German industry, and progressively so in the private sector. They must be increasingly dynamic and able to move at a speed that does not pose a danger to humans. At the same time, they should still be able to perform their tasks precisely and quickly, for example for transport in logistics. When moving fast and with a high center of gravity or when transporting high and heavy loads, the physical dynamics of the system play a major role for control engineering. It can be modeled manually, but is mostly highly abstracted from reality, which is known as the sim-to-real gap. AI and ML approaches can be used to reduce the Sim-to-Real Gap. The robot can learn a suitable model of itself, or it can take over the control entirely through reinforcement learning.