Zero Moment Control for Lead-Through Teach Programming and Process Monitoring of a Collaborative Welding Robot

Abstract

Abstract Robots are commonly used for automated welding in many industries such as automotive manufacturing. The complexity and time required for programming present an obstacle in using robotic automation in welding or other tasks for small to medium enterprises that lack resources for training or expertise in traditional robot programming strategies. It also dictates a high level of repeated parts to offset the cost of weld programming. Collaborative robots or Cobots are robots designed for more collaborative operations with humans. Cobots permit new methods of task instruction (programming) through a direct interaction between the operator and the robot. This paper presents a model and model calibration strategy for collaborative robots to aid in teaching and monitoring welding tasks. The method makes use of a torque estimation model based on robot momentum to create an observer to evaluate external forces. The torque observer is used to characterize the friction that exists within the robot joints. These data are used to define the parameters of a friction model that combines static, Coulomb, and viscous friction properties with a sigmoid function to represent a transition between motion states. With an updated friction model, the torque observer is then used for collaborative robotic welding, first to provide a mode in which the robot can be taught weld paths through physical lead through and second a mode to monitor the weld process for expected motion/force characteristics. The method is demonstrated on a commercial robot.