This paper presents a state-of-the-art optimal controller for quadruped locomotion. The robot dynamics is represented using a single rigid body (SRB) model. A linear time-varying model predictive controller (LTV MPC) is proposed by using linearization schemes. Simulation results show that the LTV MPC can execute various gaits, such as trot and crawl, and is capable of tracking desired reference trajectories even under unknown external disturbances. The LTV MPC is implemented as a quadratic program using qpOASES through the CasADi interface at 50 Hz. The proposed MPC can reach up to 1 m/s top speed with an acceleration of 0.5 m/s2 executing a trot gait. The implementation is available at https:// github.com/AndrewZheng-1011/Quad_ConvexMPC

翻译：本文展示了四振动的最先进的最佳控制器。 机器人动态代表的是一个单一的硬体( SRB) 模型。 使用线性化计划提出了线性时间分布模型预测控制器( LTV MPC ) 。 模拟结果显示, LTV MPC 能够执行各种曲目, 如Trot 和 爬行, 并且即使在未知的外部扰动下也能跟踪所需的参考轨迹。 LTV MPC 是一个二次程序, 通过位于50 Hz的 CasAdi 界面使用 qpOASES 。 拟议的MPC 最高速度可达1 m/s最高速度, 加速0. 5 m/ s2 执行一小调。 执行程序可在 https:// github.com/Andrew Zheng- 1011/ Quad_ ConexMPC 上查阅。 执行程序可在 https:// github. com/ Andreng Zheng- 1011/ Quad_ ConexMPC