Determining task optimal modular robot assembly configurations

Abstract

A "modular" robotic system consists of standardized joint and link units that can be assembled into a number of different kinematic configurations. Given a predetermined set of modules, this paper considers the problem of finding an "optimal" module assembly configuration for a specific task. The authors formulate the solution as a discrete optimization procedure. The formulation is based on an assembly incidence matrix representation of a modular robot and a general task-oriented objective function that can incorporate many realistic task criteria. Genetic algorithms (GA) are employed to solve this optimization problem, and a canonical method to represent a modular assembly in terms of genetic strings is introduced. An example involving a 3-DOF manipulator configuration is presented to demonstrate the feasibility of this approach.