Demands on leg degrees of freedom and control precision for bipedal robotics are steadily increasing, especially for the tasks involving walking on a rough terrain. In this paper we present an alternative, as well as a working proof-of-concept. Meet gyrubot: a 5-link almost planar bipedal robot with a torso complemented by a nonanthropomorphic stabilization system, capable of blindly walking through uneven areas. Despite being almost planar, the robot does not need any support in the frontal plane! This paper describes the mechanical design and the architecture of the controllers. We also provide the experimental evidence of the ability of gyrubot to navigate across non-flat terrains.

The paper centres round the problem of the engineering a motion control system for a mobile robot based on the effective selection of software components with respect to the numerical criterion proposed by the authors. The data for the selection process comes out the reproducible experiments with the sets of alternative components in a Gazebo virtual infrastructure simulating the real robot operating conditions. The genetic algorithm is used to reduce the number of experiments with unpromising sets of software components. The methodology proposed by the authors is applied to the real task of engineering a motion control system for a non-anthropomorphic mobile robot. The virtual infrastructure and genetic algorithm parameters are provided as well as the physical model of the robot for that task. To calculate the integral quality criterion proposed in the paper, 4 partial quality criteria were measured in the experiments with different software components. The motion process of the physical robot with the selected software components is shown.

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