Human operator's load force characteristics in lifting objects with a power assist robot in worst-cases conditions

Abstract

We designed a 1 DOF power assist robot for lifting objects based on human's weight perception. We hypothesized that human's perception of object weight due to inertial force might be different from the perceived weight due to gravitational force for lifting an object with a power assist robot. In this paper, we particularly studied human's load force characteristics in lifting objects with a power assist robot in worst-cases conditions. We called it a worst-case when human felt any doubt, uncertainty, sudden change in environment or unusual situation prior to or at the moment of lifting. We considered two experiments for two potential worst-cases. Subjects lifted three objects of different sizes with the robot in each experiment. In the first experiment, subject's vision was obstructed by a screen prior to lifting. In the second experiment, the object was tilted at the moment of lifting. Results of the first experiment show that when there is any doubt in feed-forward force programming, human operator considers it as the worst-case and in order to ensure the most secure fit, operator applies maximum force adequate for the largest object. Results of the second experiment show that load forces for the case when objects are tilted are larger than that when objects are placed normally. Finally, we proposed using the findings to design and control human-friendly power assist robots for carrying heavy objects in various industries such as manufacturing, mining, transport, construction etc.