Online bio-inspired trajectory generation of seven-link biped robot based on T–S fuzzy system

• Presenting a novel online method for trajectory generation of a biped robot.
• Eliminating the need to solve inverse kinematics for all points on the trajectory.
• Determining an analytical function for trajectory of all lower-body joint angles.
• Learning a fuzzy relationship between walking and CPG parameters.
• Suggesting a natural form for a ZMP trajectory to preserve the dynamic balance.

This paper proposes a novel method for real-time trajectory generation of a seven-link planar biped robot. Individual joint trajectories are generated by specifying only two key parameters, walking speed and step length. The proposed method combines several methods and concepts including kinematics, dynamics, trajectory generation, experimental design, Takagi–Suguno fuzzy systems, central pattern generator (CPG), ZMP criterion and a dynamic balance method. A fuzzy relationship between walking and CPG parameters is learned using experimental design methodology and T–S fuzzy systems. A method based on the Fourier series is used to tune parameters of the CPG. The proposed method allows making online changes to step length and walking speed while ensuring robot's dynamic balance. A multibody simulation package is selected and the effectiveness of the method is illustrated using several examples. It is also shown that changes in joint angles, as the result of online changes to the walking parameters, occur in a smooth and continuous manner.

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