We introduce novel methods for state estimation, feedforward and feedback control, which specifically target humanoid robots with hardware limitations. Our method combines a five-mass model with approximate dynamics of each mass. It enables acquiring an accurate assessment of the centroidal state and Center of Pressure, even when direct forms of force or contact sensing are unavailable. Upon this, we develop a feedforward scheme that operates on the centroidal state, accounting for insufficient joint tracking capabilities. Finally, we implement feedback mechanisms, which compensate for the lack in Degrees of Freedom that our NimbRo-OP2X robot has. The whole approach allows for reactive stepping to maintain balance despite these limitations, which was verified on hardware during RoboCup 2023, in Bordeaux, France.

翻译：我们提出了针对具有硬件限制的仿人机器人的状态估计、前馈与反馈控制的新型方法。该方法结合了五质量模型与各质量的近似动力学，可在缺少直接力或接触传感方式的情况下，实现对质心状态与压力中心的精确评估。基于此，我们开发了一种作用于质心状态的前馈方案，以应对关节跟踪能力不足的问题。最后，我们实现了反馈机制，用于补偿NimbRo-OP2X机器人自由度缺失的缺陷。整套方法允许机器人在这些限制下通过反应式迈步维持平衡，并于2023年在法国波尔多举行的RoboCup比赛中通过硬件验证。