Assembly task planning for a dual-arm robot using the configuration space decomposition method

Abstract

The previous industrial robot has been used mainly for simple and repetitive tasks such as welding and transferring. However, in recent years, the dual-arm robots have been developed for complicated work in several institutions. These dual-arm robots mainly demonstrate the assembly task of several products. In the assembly task, a robot needs to be taught by a human or to be given a preprogrammed path. However, manual teaching or programming by a human is a heavy load of many types of products. Therefore, this thesis proposes the path planning scheme of the dual-arm robot for the assembly task. In this thesis, the assembly task is defined as to combine multiple parts into one. The attachment task such as welding or bonding is not treated. It is assumed that if one part reaches the assembly position, it will be fixed to the position. The input data of the algorithm are the relative assembly position between the parts, the initial positions of the parts, the sequence of the assembly parts, the geometrical data of the parts, the grasp position lists of the parts, and the initial configuration of the robot. It is also considered that, because two parts are complicated, the movement of dual-arm is restricted to avoid collisions. The assembly task involving such complex parts by the dual-arm robot conducted in configuration space tends to require the heavy computational load, and conventional path planning methods have limits in the aspect of computational time. Thus, this thesis suggested the path planning algorithm of the dual-arm robot in operational space for the assembly task involving complex parts and conducted the simulations to verify the effectiveness of the suggested method. The results show that the suggested path planning method on operational space is more effective compared to the conventional path planning method in configuration space, particularly in aspects of the computational time.