Generation Method of Robot Assembly Motion Considering Physicality Gap Between Humans and Robots

In this study, we propose a method for simplifying the assigning of robot motion parameters as this task is very time consuming. Parts used in a factory have different shapes and sizes but are categorized under the same name. With the proposed method, the robot's grasping point for one part is determined using a human's optimal grasping point for another part as a cue. The novelty of our method is that we consider the physicality gap between humans and robots as well as the functions of industrial parts. An example of this gap is the difference between a human and robot's hand shape. A function refers to the role of each component of an industrial part. Grasping points are determined from the grasping function of a target part using features related to the physicality gap. In an experiment using connecting rods, the average success rate of robot motions with the method was 82.8%.