Task-based optimization of modular robot configurations: minimized degree-of-freedom approach

A modular robot system consists of a collection of individual link and joint components that can be assembled into many different robot configurations. With fewer number of modules and degrees of freedom, a modular robot would have a simple configuration, high loading capacity, and low power consumption rate, so that it can perform the task effectively. In this article, the Minimized Degree-Of-Freedom (MDOF) concept is introduced for the optimization of modular reconfigurable robot configurations for specific task requirements. The MDOF problem is formulated as a design optimization problem. A weighted sum of the numbers of different types of modules in a robot is chosen as the objective function. Several task-related kinematic performance measures are considered as the design constraints. Based on the problem specific coding schemes, the evolutionary algorithm (EA) approach is employed to search for the optimal solutions. A virtual module concept is also introduced into the coding schemes in order to guarantee the operation of EA when performing both topology and dimension designs simultaneously. The effectiveness of this approach is demonstrated by computation examples.