Abstract
A new approach to robotic high precision selective assembly is presented. The basis for this selective assembly is a gripper which both grips the part to be assembled along its mating planes and inspects its dimensions while gripping. One hundred percent interchangeability of spare parts is achieved by selecting the appropriate parts for inventory, during assembly. Cost reduction and the increase in product quality are shown by example.
Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly