Wu Yao, Tang Biao, Tang Jiawei, Qiao Shuo, Pang Xiaobing, Guo Lei
School of Mechatronic Engineering, Changsha University, Changsha 410022, China.
School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China.
Biomimetics (Basel). 2024 Oct 15;9(10):626. doi: 10.3390/biomimetics9100626.
In order to improve the walking stability of a biped robot in multiple scenarios and reduce the complexity of the Central Pattern Generator (CPG) model, a new CPG walking controller based on multivariate linear mapping was proposed. At first, in order to establish a dynamics model, the lower limb mechanical structure of the biped robot was designed. According to the Lagrange and angular momentum conservation method, the hybrid dynamic model of the biped robot was established. The initial value of the robot's passive walking was found by means of Poincaré mapping and cell mapping methods. Then, a multivariate linear mapping model was established to form a new lightweight CPG model based on a Hopf oscillator. According to the parameter distribution of the new CPG model, a preliminary parameter-tuning idea was proposed. At last, the joint simulation of MATLAB and V-REP shows that the biped robot based on the new CPG control has a stable periodic gait in flat and uphill scenes. The proposed method could improve the stability and versatility of bipedal walking in various environments and can provide general CPG generation and a tuning method reference for robotics scholars.
为了提高双足机器人在多种场景下的行走稳定性并降低中枢模式发生器（CPG）模型的复杂度，提出了一种基于多元线性映射的新型CPG行走控制器。首先，为建立动力学模型，设计了双足机器人的下肢机械结构。根据拉格朗日方法和角动量守恒方法，建立了双足机器人的混合动力学模型。通过庞加莱映射和胞映射方法找到了机器人被动行走的初始值。然后，建立多元线性映射模型，基于霍普夫振荡器形成新型轻量级CPG模型。根据新型CPG模型的参数分布，提出了初步的参数调整思路。最后，MATLAB和V-REP的联合仿真表明，基于新型CPG控制的双足机器人在平坦和上坡场景中具有稳定的周期性步态。所提方法可提高双足行走在各种环境下的稳定性和通用性，并可为机器人学者提供通用的CPG生成及调整方法参考。
