Figure 1. Schematic representation of our OFC-LD approach.

The optimal controller requires a cost function, which here encodes for reaching time, endpoint accuracy, endpoint velocity (i.e., stability), and energy efficiency. Further a forward dynamics function is required, which in OFC-LD is learned from plant feedback directly. This learned internal dynamics function not only allows us to model changes in the plant dynamics (i.e., adaptation) but also encodes for the uncertainty in the dynamics data. The uncertainty itself, visible as kinematic variability in the plant, can originate from different sources, which we here classify into external sources and internal sources of uncertainty. Most notably OFC-LD identifies the uncertainty directly from the dynamics data not making prior assumptions about its source or shape.