On input-output linearization of mobile robots with nonholonomic constraints

Articulated-body mobile robotic systems are becoming more important in many applications, because of the appeal of snakelike structure of these systems. The dynamics of articulated mobile systems, however, may lead to nonholonomic constraints, due to the physical geometry of the platforms. An appealing approach to robot control is the method of input-output linearization whereby the nonlinear robotic system is made globally linear equivalent through an inverse dynamics compensator, The difficulty with robotic systems with nonholonomic constraints is that the inverse dynamics do not exist and therefore linearization is not possible. In this paper, an output transformation is developed to replace the geometric singularity with dynamics in which the inverse dynamics exist; thus global linearization is possible and linear or nonlinear controller may be designed, based upon the linear equivalent structure. An example using the model of the Mars Mission Research Center experimental rover and a neural network controller is presented to illustrate the feasibility of this approach.