Push Recovery by Angular Momentum Control during 3D Bipedal Walking based on Virtual-mass-ellipsoid Inverted Pendulum Model

SUMMARY The work aims to realize energy-efficient bipedal walking by employing the three-mass inverted pendulum model (3MIPM) and compare its energy performance with linear inverted pendulum model (LIPM). To do this, a general optimal index on center of mass (CoM) acceleration is first derived for energetic cost evaluation. After defining the equivalent zero moment point (ZMP) motion, an unconstrained optimization approach for CoM generation is extended for 3MIPM, which can track different ZMP references and address the height variation as well. To make use of the allowable ZMP movement, a constrained optimization method is also employed, contributing to lower energetic cost. Simulation and hardware experiments on a humanoid robot demonstrate that the 3MIPM could achieve higher energy efficiency.

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Orbit Characterization, Stabilization and Composition on 3D Underactuated Bipedal Walking via Hybrid Passive Linear Inverted Pendulum Model

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros40897.2019.8968162 ◽

2019 ◽

Cited By ~ 1

Author(s):

Xiaobin Xiong ◽

Aaron D. Ames

Keyword(s):

Inverted Pendulum ◽

Bipedal Walking ◽

Inverted Pendulum Model ◽

Pendulum Model

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Robust Stability Control of Inverted Pendulum Model for Bipedal Walking Robot

Al-Nahrain Journal for Engineering Sciences ◽

10.29194/njes.23010081 ◽

2020 ◽

Vol 23 (1) ◽

pp. 81-88

Author(s):

Ali Fawzi Abdul Kareem ◽

Ahmed Abdul Hussein Ali

Keyword(s):

Inverted Pendulum ◽

Bipedal Walking ◽

Phase System ◽

Minimum Phase ◽

Walking Robot ◽

Point Tracking ◽

Inverted Pendulum Model ◽

Noise Rejection ◽

Pendulum Model ◽

Zero Moment

This paper proposes robust control for three models of the linear inverted pendulum (one mass linear inverted pendulum model, two masses linear inverted pendulum model and three masses linear inverted pendulum model) which represents the upper, middle and lower body of a bipedal walking robot. The bipedal walking robot is built of light-weight and hard Aluminum sheets with 2 mm thickness. The minimum phase system and non-minimum phase system are studied and investigated for inverted pendulum models. The bipedal walking robot is programmed by Arduino microcontroller UNO. A MATLAB Simulink system is built to embrace the theoretical work. The results showed that one linear inverted pendulum is the worst performance, worst noise rejection and the worst set point tracking to the zero moment point. But two masses linear inverted pendulum models and three masses linear inverted pendulum model have a better performance, a better high-frequency noise rejection characteristic and better set-point tracking to the zero moment point.

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Capture Steps: Robust Walking for Humanoid Robots

International Journal of Humanoid Robotics ◽

10.1142/s0219843619500324 ◽

2019 ◽

Vol 16 (06) ◽

pp. 1950032 ◽

Cited By ~ 1

Author(s):

Marcell Missura ◽

Maren Bennewitz ◽

Sven Behnke

Keyword(s):

Degrees Of Freedom ◽

Center Of Mass ◽

Humanoid Robots ◽

Open Loop ◽

Bipedal Walking ◽

Foot Placement ◽

Inverted Pendulum Model ◽

Push Recovery ◽

Pendulum Model ◽

Walking Velocity

Stable bipedal walking is a key prerequisite for humanoid robots to reach their potential of being versatile helpers in our everyday environments. Bipedal walking is, however, a complex motion that requires the coordination of many degrees of freedom while it is also inherently unstable and sensitive to disturbances. The balance of a walking biped has to be constantly maintained. The most effective ways of controlling balance are well timed and placed recovery steps — capture steps — that absorb the expense momentum gained from a push or a stumble. We present a bipedal gait generation framework that utilizes step timing and foot placement techniques in order to recover the balance of a biped even after strong disturbances. Our framework modifies the next footstep location instantly when responding to a disturbance and generates controllable omnidirectional walking using only very little sensing and computational power. We exploit the open-loop stability of a central pattern generated gait to fit a linear inverted pendulum model (LIPM) to the observed center of mass (CoM) trajectory. Then, we use the fitted model to predict suitable footstep locations and timings in order to maintain balance while following a target walking velocity. Our experiments show qualitative and statistical evidence of one of the strongest push-recovery capabilities among humanoid robots to date.

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