Balanced Standing on One Foot of Biped Robot Based on Three-Particle Model Predictive Control

Abstract

Balancing is a fundamental task in the motion control of bipedal robots. Compared to two-foot balancing, one-foot balancing introduces new challenges, such as a smaller supporting polygon and control difficulty coming from the kinematic coupling between the center of mass (CoM) and the swinging leg. Although nonlinear model predictive control (NMPC) may solve this problem, it is not feasible to implement it on the actual robot because of its large amount of calculation. This paper proposes the three-particle model predictive control (TP-MPC) approach. It combines with the hierarchical whole-body control (WBC) to solve the one-leg balancing problem in real time. The bipedal robot’s torso and two legs are modeled as three separate particles without inertia. The TP-MPC generates feasible swing leg trajectories, followed by the WBC to adjust the robot’s center of mass. Since the three-particle model is linear, the TP-MPC requires less computational cost, which implies real-time execution on an actual robot. The proposed method is verified in simulation. Simulation results show that our method can resist much larger external disturbance than the WBC-only control scheme.

Research on Walking Gait Planning and Simulation of a Novel Hybrid Biped Robot

“…ZMP is a commonly used method for determining the stable state of the wa ing motion of bipedal robots. The definition of ZMP can be obtained from the literatu mimetics 2023, 8, x FOR PEER REVIEW 14 of 1 [21,22]. Usually, when the ZMP is in the sole support region of a bipedal robot, the motion state of the robot can be considered stable.…”

A Multi-Agent Reinforcement Learning Method for Omnidirectional Walking of Bipedal Robots

“…These traditional techniques exhibit high computational complexity, low robustness, and poor generality. While Model Predictive Control (MPC) is not classified as a traditional gait control method, its wide application in bipedal robot gait control is noticeable [12]. Reference [13] proposes a holistic MPC scheme based on differential dynamic programming to tackle the challenges of physical constraints and model discrepancies in bipedal robots.…”