An algorithm of foot end trajectory tracking control for quadruped robot based on model predictive control
The control of the leg mechanism of the quadruped robot has always been one of the research hotspots in the field of robotics. This paper proposes to use the model predictive control method (MPC) to control the foot track tracking of the quadruped robot. Using the Newton-Euler formula to model the dynamics of the leg mechanical structure and obtaining its discrete linear state space model. According to the performance indicators and constraints given by the system, the actual output is feedback corrected to achieve real-time tracking of the required joint rotation angle trajectory.
The study of human gait remains one of the finest areas of biomechanics. Commonly available gait characterization systems provide information regarding speed, cadence and calories burnt during an exercise session. However, the gait of an individual changes continuously with every step. Thus, this work is inspired by the need to develop a system which enables real time analysis of critical spatio-temporal gait parameters while adapting to the walking pattern of the subject. The study of these parameters for a given subject enables us to perform an analysis of individualized gait pattern thereby allowing us to develop corrective measures for gait deficits. In this work we present a real-time analysis of intra-limb temporal parameters using the proposed system that adapts to the changing walking speed. 1