A tree-shaped motion strategy for robustly executing robotic assembly tasks

Abstract

An assembly robot needs to be capable of executing an assembly task robustly under various uncertainties. To attain this goal, we use a task sequence tree model originally proposed for manual assembly. This model regards an assembly task under uncertainties as a transformation of the contact state concept. The concept may contain several contact states with probabilities but these are transformed through a series of task elements into the contact state concept having only the goal state at the end. The transformed contact state concept can be classified according to the terminal condition of each task element. Thus, the whole assembly task can be designed as a tree-shaped contingent strategy called a task sequence tree. This paper proposes a systematic approach for reconfiguring a task sequence tree model for application to a robotic assembly task. In addition, by taking a 2D peg-in-hole insertion task to be performed by a robot equipped with a force sensor as an example, we confirm that the proposed approach can provide a robust motion strategy for the task and that the robot can actually execute the task robustly under bounded uncertainty according to the strategy.