Xu Zihan, Fang Qin, Liu Chengju, Chen Qijun
Robot and Artificial Intelligence Lab (RAIL), College of Electronic and Information Engineering, Tongji University, No. 4800 Cao'an Road, Shanghai 201804, China.
Tongji Artificial Intelligence (Suzhou) Research Institute, Suzhou 215000, China.
Biomimetics (Basel). 2023 Mar 2;8(1):100. doi: 10.3390/biomimetics8010100.
For biped robots, the ability to maintain balance under external forces is an essential requirement. Inspired by human beings' behaviors to resist external forces, a compliant-resistant balance-control method is proposed to keep the biped robot balance subjected to an external force. A model-free trajectory generator is designed based on the central pattern generator (CPG) to generate compliant-resistant human-like behavior. The CPG pattern generator generates the desired pulse signal utilizing Matsuoka's CPG. The signal modulator applies the defined signal to the robot's center of mass (CoM) to generate the workspace trajectory when standing on double feet. Moreover, when standing on single foot, the output signal of the CPG will directly act on the hip joint of the robot to generate the joint space trajectory. Furthermore, the motion engine calculates the workspace trajectory into joint sequence values. The proposed control strategy can generate defined pulse signals to realize compliant-resistant balance control for biped robots. The control strategy proposed in this paper is verified in the NAO simulation environment.
对于双足机器人而言，在外力作用下保持平衡的能力是一项基本要求。受人类抵抗外力行为的启发，提出了一种柔顺抵抗平衡控制方法，以使双足机器人在受到外力时保持平衡。基于中枢模式发生器（CPG）设计了一种无模型轨迹生成器，以生成类似人类的柔顺抵抗行为。CPG模式发生器利用松冈的CPG生成所需的脉冲信号。信号调制器将定义的信号应用于机器人的质心（CoM），以在双脚站立时生成工作空间轨迹。此外，当单脚站立时，CPG的输出信号将直接作用于机器人的髋关节，以生成关节空间轨迹。此外，运动引擎将工作空间轨迹计算为关节序列值。所提出的控制策略可以生成定义的脉冲信号，以实现双足机器人的柔顺抵抗平衡控制。本文提出的控制策略在NAO仿真环境中得到了验证。
