An optimal closed-loop framework to develop stable walking for humanoid robot
Mohammadreza Kasaei, Nuno Lau, Artur Pereira
- 发表年份
- 2018
- 引用次数
- 19
摘要
Bipedal robots are essentially unstable because of their complex kinematics as well as high dimensional state space dynamics, hence control and generation of stable walking is a complex subject that is still one of the active topics in the robotic community. This paper proposes a closed-loop model-based walk engine which takes into account push recovery strategies. In this paper, Linear Inverted Pendulum Plus Flywheel Model (LIPPFM) is extended and used to approximate the overall dynamics of a humanoid robot. We extended this model by releasing the height constraint of the center of mass (COM) as well as by considering the mass of pendulum to increase the accuracy of the model. In this framework, a step is composed of a double support phase in addition to a single support phase. Moreover, ZMP and reference trajectory generators are formulated based on the input parameters and tracking problem are formulated as a finite-time horizon linear quadratic regulator (LQR) problem. The proposed framework has been successfully tested by performing several simulations using MATLAB. The simulation results show this framework is capable to provide stable walking on an uneven terrain.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002