Haptics of Screwing and Unscrewing for its Application in Smart Factories for Disassembly
This addresses automation in smart factories for disassembly, but is incremental as it applies known human strategies to robotics.
The paper tackled the problem of robot disassembly by analyzing human haptic patterns during screwing and unscrewing, finding that axial force is proportional to torque and varies with screw head type, and used this to develop an unscrewing robot with confirmed optimality.
Reconstruction of skilled humans sensation and control system often leads to a development of robust control for the robots. We are developing an unscrewing robot for the automated disassembly which requires a comprehensive control system, but unscrewing experiments with robots are often limited to several conditions. On the contrary, humans typically have a broad range of screwing experiences and sensations throughout their lives, and we conducted an experiment to find these haptic patterns. Results show that people apply axial force to the screws to avoid screwdriver slippage (cam-outs), which is one of the key problems during screwing and unscrewing, and this axial force is proportional to the torque which is required for screwing. We have found that type of the screw head influences the amount of axial force applied. Using this knowledge an unscrewing robot for the smart disassembly factory RecyBot is developed, and experiments confirm the optimality of the strategy, used by humans. Finally, a methodology for robust unscrewing algorithm design is presented as a generalization of the findings. It can seriously speed up the development of the screwing and unscrewing robots and tools.