Force Plates for Analyzing, Recording and Teaching Forces of Dis-/Assembly Processes for Robot Programming-by-Demonstration

Assembly tasks remain a challenge for industrial robots, as they involve physical contact where small path deviations can cause irreversible damage. While force control can mitigate such issues, tuning control parameters requires expert knowledge. Learning-from-Demonstration (LfD) or Imitation Learning (IL) offers a more intuitive alternative, but most force-based approaches rely on hand-guiding, requiring expensive cobots or raising safety concerns. Observation-based methods, in contrast, often depend on cameras and are limited to position control, suffering from occlusions and inaccuracies.We propose a novel tool that estimates position from force signals, without cameras or direct robot interaction, to enable force-based programming of assembly tasks. Using a network of four force-torque sensors, our system detects contact position, direction, and magnitude, achieving sub-millimeter accuracy (< 1 mm) in relevant areas. Demonstrations include the force-based assembly of a snap-fit, occluded plug insertion, and terminal clamp assembly. A user study with 20 participants shows that our approach reduces teaching time for terminal clamps by 61% compared to hand-guided methods, and lowers both mental load and perceived frustration by over 40% each.