Bipedal walking pattern generation and control for humanoid robot with bivariate stability margin optimization

Yang, Liang; Li, Zhi; Chen, Yong

doi:10.1177/1687814018800883

Cited by 5 publications

(3 citation statements)

References 31 publications

(55 reference statements)

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“…However, this does not guarantee the tracking of the CoG of the robot at the desired precision level. The CoG is in the middle of the connection points of the two legs of the robot or at a higher position [18][19][20][21][22][23][24][25]. The position of the CoG is calculated before the robot starts its motion.…”

Section: Introductionmentioning

confidence: 99%

Precise Inverse Kinematic Calculation of the Center of Gravity for Bipedal Walking Robots

Şanlıtürk,

Kocabaş

2024

Preprint

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Walking of humanoid robots is dependent on precise tracking of the center of gravity and foot trajectories. Trajectory tracking is achieved by mobilizing the robot joints to produce the correct trajectory. Errors are being occurred because of assumptions on tracking the center of gravity and the foot trajectories. In this study, a numerical algorithm has been developed that produces an exact and single kinematic solution in which the center of gravity and foot trajectories can be tracked with the desired precision. The effectiveness of the algorithm was examined with a dynamic simulation and compared with the method given in the literature The main highlight of this study, using the presented algorithm, the robot can walk even if the position of its center of gravity is lower than its hips, resulting tracking error was smaller than reported in the literature.

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Section: Introductionmentioning

confidence: 99%

Precise Inverse Kinematic Calculation of the Center of Gravity for Bipedal Walking Robots

Şanlıtürk,

Kocabaş

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…However, this does not guarantee the tracking of the CoG of the robot at the desired precision level. The CoG is in the middle of the connection points of the two legs of the robot or at a higher position [18][19][20][21][22][23][24][25]. The CoG is calculated before the robot starts its motion.…”

Section: Introductionmentioning

confidence: 99%

Precise Calculation of Inverse Kinematics of the Center of Gravity for Bipedal Walking Robots

Şanlıtürk,

Kocabaş

2024

Applied Sciences

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The walking of humanoid robots is dependent on the precise tracking of their center of gravity and foot trajectories. Trajectory tracking is achieved by mobilizing their joints to achieve the correct trajectory. Errors occur because of assumptions on tracking the center of gravity and the foot trajectories. In this study, a numerical algorithm was developed that produces an exact and single kinematic solution in which the center of gravity and foot trajectories can be tracked with the desired precision. The effectiveness of this algorithm was examined with a dynamic simulation and compared with a method given in the literature. The main highlight of this study, using the presented algorithm, is that the robot could walk even if the position of its center of gravity was lower than its hips, resulting in a tracking error that was smaller than that reported in the literature.

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“…Kai Hu et al [6] designed Compensative Zero-Moment Point Trajectory from the reference ZMP to decrease the effect of disturbances. Likewise, Yang et al [7] presented bivariatestability-margin-based control model to compensate zero moment point and modeling error, opposition-based learning algorithm is applied to generated gait pattern.…”

Section: Introductionmentioning

confidence: 99%

Applying Improve Differential Evolution Algorithm for Solving Gait Generation Problem of Humanoid Robots

Nguyen¹,

Bui²

2021

Robotics Software Design and Engineering

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This chapter addresses an approach to generate 3D gait for humanoid robots. The proposed method considers gait generation matter as optimization problem with constraints. Firstly, trigonometric function is used to produce trial gait data for conducting simulation. By collecting the result, we build an approximation model to predict final status of the robot in locomotion, and construct optimization problem with constraints. In next step, we apply an improve differential evolution algorithm with Gauss distribution for solving optimization problem and achieve better gait data for the robot. This approach is validated using Kondo robot in a simulated dynamic environment. The 3D gait of the robot is compared to human in walk.

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Bipedal walking pattern generation and control for humanoid robot with bivariate stability margin optimization

Cited by 5 publications

References 31 publications

Precise Inverse Kinematic Calculation of the Center of Gravity for Bipedal Walking Robots

Precise Inverse Kinematic Calculation of the Center of Gravity for Bipedal Walking Robots

Precise Calculation of Inverse Kinematics of the Center of Gravity for Bipedal Walking Robots

Applying Improve Differential Evolution Algorithm for Solving Gait Generation Problem of Humanoid Robots

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