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Hybrid CPG–FRI dynamic walking algorithm balancing agility and stability control of biped robot

  • Bin HeEmail author
  • Yuanyuan Si
  • Zhipeng WangEmail author
  • Yanmin ZhouEmail author
Article
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Abstract

Dynamic walking fulfill agility and stability simultaneously is one of the most difficulty for biped robot control. The traditional zero moment point (ZMP) is the most commonly used reference point for biped robot static and quasi dynamic walking control. However, human walking experimental results indicate that during walking process of human beings, the ZMP trajectory is not always conformed to the requirement of stability, such as giant strides, acceleration walking or fast walking. In order to reveal the mechanism of the biped dynamic walking, this paper proposed a novel stability criterion for the biped walking by tuning the conventional fixed support polygon area to an adjustable one. This method includes the tiptoe underactuated phase of the support foot during the biped walking. A new algorithm for the real-time biped walking generation by combining central pattern generation (CPG) with foot rotation indicator (FRI) is presented. The FRI monitor establishes the mapping function between the center of mass of the biped robot with the boundary of the elastic support polygon. By introducing FRI information, the CPG parameters can be adjusted in real time to generate a rhythmic and stable walking pattern. Numerical simulation results show that the proposed algorithm extends the application area of the ZMP criterion and improves the walking velocity of the biped robot. Moreover, the algorithm builds a bridge for the dynamic biped walking from the robot agility to motor parameters. This means that the agility of the biped robot can be quantitative controlled by modulating the motor parameters.

Keywords

Biped robot Foot rotation indicator Central pattern generator Stability control Elastic support polygon Dynamic walking 

Notes

Acknowledgements

The work was supported by National Natural Science Foundation of China (Grant Nos. 51605334, U1713215, and 51705368), and Shanghai Municipal Science and Technology Commission Project (Grant No. 17DZ1203405). We thank the reviewers and editors for their helpful comments on the manuscript.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Control Science and EngineeringTongji UniversityShanghaiChina

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