This paper is motivated to transfer the model predictive control approach used in bipedal locomotion to formulate gait planning of quadrupedal robots. The particular lateral-sequence gait of quadrupeds is treated as an equivalence to the bipedal walking. The Model Predictive Control (MPC) algorithm uses 3D-Linear Inverted Pendulum Model for representing the center of mass dynamics for planning the quadrupedal gaits, and a dimensionless discretetime state-space formulated is derived for MPC. Subsequently, the footholds can be generated automatically via optimization of quadratic programming (QP) without the need of a separate footstep planner. The generated walking gaits were implemented and validated first in the physics simulation of a quadruped named EHbot, and then the effectiveness of the proposed method was further
demonstrated through our experiments. Both simulation and experimental data are presented and analyzed for evaluating the performance.