Online Foot Location Planning for Gait Transitioning Using Model Predictive Control

Abstract

This paper proposes an online uniform foot location planning method (UPMPC) based on model predictive control (MPC) for solving the problem of large posture changes during gait transitioning. This method converts the foot location planning into a discrete-time MPC problem. The core part of the method is to complete the planning of the foot location based on the linear inverted pendulum (LIP) model and the simplified robot dynamics model. By unifying the input foot location at each time step, the solution time is shortened. The final simulation experiment compares the results of using the UPMPC and foot location planning method with heuristic function (HF) for gait transitioning, respectively. This result demonstrates that the UPMPC can complete the gait transitioning task and adapt to large changes in posture during gait transitioning. In addition, the results also show the good performance of UPMPC in fixed gait.

Reduced Model Predictive Control Toward Highly Dynamic Quadruped Locomotion

“…Note that the planar kinematics ( 12) comprises a left term associated with the foot trajectory with respect to body coordinates and right terms that account for forward, lateral, and yaw motions, which are absent in the reduced SRBM. This implies that the foot trajectory can be designed based on (12), enabling the implementation of the desired omnidirectional motion.…”

“…While the robot follows its designed trajectory, undesirable motions may arise due to unmodeled factors in the planar kinematics (12). These undesirable motions have the potential to adversely affect the balance of the robot, making it imperative to control and regulate them.…”

“…These methods represent the center of mass (COM) trajectory of the IPM as polynomials. Some researchers have even explored the direct use of the COM trajectory as a decision variable in MPC, although these efforts have primarily been limited to simulations [9]- [12]. Besides the IPM, other MPC studies have utilized simpler models, such as those involving the ground projection of the COM, which have exhibited robust control performance for slow quadrupedal locomotion [13], [14].…”

Modelling and Control of Mechatronic and Robotic Systems, Volume II

“…That control algorithm solves the problem of model uncertainty when the number of connecting rods of the serpentine manipulator increases and the environment becomes complex. Moreover, the model of a quadruped robot is considered in [11] to demonstrate the performance of an online foot-location-planning approach for legged robots. In particular, the illustrated strategy leverages model predictive control to solve the problem of large posture changes during gait transitions.…”