Natural Walking Trajectory Generator for Humanoid Robot Based on Three-Mass LIPFM

• Published in: IEEE access Vol. 8; pp. 228151 - 228162
• Main Authors: Wong, Ching-Chang, Xiao, Sheng-Ru, Aoyama, Hisasuki
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Angular momentum; biped walking; center of mass (CoM); Dynamic models; Flywheels; Humanoid; Humanoid robot; Humanoid robots; Legged locomotion; linear inverted pendulum model (LIPM); Mass distribution; Mathematical model; Pendulums; Robot dynamics; Robot kinematics; Robots; Thigh; Trajectory; Walking; zero moment point (ZMP)
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3046106

In this paper, a dynamic model named Three-mass Linear Inverted Pendulum plus Flywheel Model (TLIPFM) is proposed to approximate the walking motion of the humanoid robot. The mass distribution of the robot and the angular momentum of the robot are simultaneously considered to construct the dynamic model. In the mass distribution of the robot, the overall robot is divided into three parts: 1) the whole upper body of the robot, 2) the thigh of the robot's support leg, and 3) the calf of the robot's support leg, and these three weights are considered to be three masses in the proposed TLIPFM. In the angular momentum of the robot, a flywheel joint is configured at the Center of Mass (CoM) of the robot to obtain the rotational torque of the robot in biped walking. In addition, a natural walking trajectory generator based on the TLIPFM and a moving Zero Moment Point (ZMP) reference is derived to generate ZMP trajectory, CoM trajectory, and foot trajectory in three-dimensional space to let the humanoid robot walk stably. In the experiment, some results are presented to illustrate that the proposed TLIPFM can effectively reduce the model error and the proposed TLIPFM-based walking trajectory generator makes the walking trajectories more natural and walking more stable. Moreover, the proposed method is implemented on a real small-sized humanoid robot to illustrate its feasibility and practicability for the real-time biped walking.