In a joint research project with a premium car manufacturer, we have managed to show that a laser welding robot can recognize its own behavior and independently improve according to indicators it has been provided with.
A robot does what an engineer has tasked it to do. These days, it is usually the case that in practice defined parameter records are produced out of a few test runs which uniquely define the operational behavior of the robot. The best record is selected in accordance with certain KPIs and implemented in the subsequent operation. Currently, the 'right' parameter records are found by carrying out a few test runs with the laser welding robots under the instruction of an engineer.
In everyday operation, however, a robot's environment in a factory is subject to change and the tasks of a robot may vary, too. Imagine if the welding robot autonomously optimized its behavior accordingly so that the engineer only needed to tell the robot what the requirements are for a component or a weld seam? In this scenario, the robots would then find a systematic way to meet the requirements in various situations by themselves.