Integrated optimization design and motion control of multi-configuration unmanned metamorphic vehicle

Abstract

An unmanned metamorphic vehicle is a new deformable robot that can transform its configuration according to different road conditions in order to realize wheeled driving or legged walking. This paper proposes a method of multi-objective integrated optimization design based on the motion control of unmanned metamorphic vehicle. The aim of this method is to improve the stability and reduce energy consumption of multi-configuration motion. The vehicle state configuration and the humanoid state walking performance were designed. The kinematic model of reconfiguration and humanoid walking was established from screw theory, while the Lagrangian dynamics model for reconfiguration and humanoid walking using analytical mechanics. Reconfiguration and gait planning were carried out for an unmanned metamorphic vehicle, and a sliding mode controller was designed for position feedback control of the zero moment point in order to improve the stability of reconfiguration and walking. In order to improve the kinematic performance of an unmanned metamorphic vehicle under multiconfiguration, the NSGA-II intelligent optimization algorithm was used to optimize the multi-objective integrated design of the structural parameters, posture parameters, and control parameters of the sliding mode controller of the system. The simulation and test results showed that the integrated design performs higher reconfiguration stability, lower energy consumption, and higher control quality than the sequential design and pre-optimization under the reconfiguration condition; in the vehicle state, the transient steering stability and the steady-state steering stability of the system during driving are significantly improved; in the humanoid state, the energy consumption of the striding process and the movement of the center of mass to the single-legged support region in the walking process is reduced and the walking stability is improved, thus is more conducive to walking.