Abstract

In this paper, a real-time balance control method is designed and implemented on a field-programmable gate array (FPGA) chip for a small-sized humanoid robot. In the proposed balance control structure, there are four modules: (1) external force detection, (2) push recovery balance control, (3) trajectory planning, and (4) inverse kinematics. The proposed method is implemented on the FPGA chip so that it can quickly respond to keep the small-sized humanoid robot balanced when it is pushed by external forces. A gyroscope and an accelerometer are used to detect the inclination angle of the robot. When the robot is under the action of an external force, an excessively large inclination angle may be produced, causing it to lose its balance. A linear inverted pendulum with a flywheel model is employed to estimate a capture point where the robot should step to maintain its balance. In addition, the central pattern generators (CPGs) with a sinusoidal function are adopted to plan the stepping trajectories. Some experimental results are presented to illustrate that the proposed real-time balance control method can effectively enable the robot to keep its balance to avoid falling down.

Highlights

  • Compared with wheeled robots, a biped structure and excellent athletic ability are given to humanoid robots

  • When the balance control method is disabled, the experimental results of the TKU-X robot hit from the back by a baseball and a volleyball are shown in Figure 13a,b, respectively

  • A push recovery balance control method is proposed and implemented based on a linear inverted pendulum with a flywheel model to enable the humanoid robot to regain its balance when a strong enough external force is measured by the proposed external force detection method

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Summary

Introduction

A biped structure and excellent athletic ability are given to humanoid robots. The zero moment point (ZMP) and walking dynamics analysis can be adopted to enable a robot to walk steadily [4,5,6,7]. These methods require copious calculations; researchers must develop an approximate or simple dynamic model. The regular rhythmic motion is produced by the steady walking gaits so that the characteristics of the oscillator are suitable for presenting CPGs in the workspace [12]. Several kinds of research have employed ZMP or attitude estimation to examine whether the robot motion followed the walking model created by CPGs [13], and the

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