Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/33314
Title: Augmented Linear Inverted Pendulum Model for Bipedal Gait Planning
Authors: DAU VAN HUAN
Keywords: humanoid robot, foot placement indicator, genetic algorithm, ZMP, bipedal walking,
Issue Date: 2-Aug-2011
Source: DAU VAN HUAN (2011-08-02). Augmented Linear Inverted Pendulum Model for Bipedal Gait Planning. ScholarBank@NUS Repository.
Abstract: This thesis proposes a new model called the Augmented Linear Inverted Pendulum (ALIP) for bipedal walking. In this model, an augmented function $F$ is added to the dynamic equation of the Linear Inverted Pendulum. The role of the augmented function is to improve the inverted pendulum dynamics by indirectly incorporating the dynamics of the arms, legs, heads, etc into the dynamics equation. The inverted pendulum dynamics can be easily adjusted or modified by changing the key parameters of the augmented function. Genetic algorithm is used to find the optimal value of the key parameters of the augmented function. Our objective is to design a walking pattern that has the highest stability margin possible. The proposed ALIP model was used to generate off-line walking pattern for biped robot in 2D and 3D walking. Simulation results show that the proposed ALIP model is able to generate highly stable walking patterns. The walking patterns generated using the proposed approach is more stable than that generated using the LIPM model and GCIPM (an improved version of the LIPM model) model. The ankle control strategy was proposed to improve stability margin. In this strategy, the ankle joint is controlled such that the ZMP stays as close to the middle point of the supporting foot as possible. This is obtained by adjusting the ankle pitch and roll angles based on the ground reaction force information so that the difference between the ground reaction force at the heel and toe is minimized. Simulation results show that the proposed method is effective in increasing the stability margin of the bipedal walking robot. The proposed ALIP model was also successfully applied to generate online walking motion in sagittal plane. The online walking algorithm comprises of a proposed function called the Foot Placement Indicator (FPI). The Foot Placement Indicator (FPI) is an important part of the online walking algorithm. The role of the FPI is to decide the next walking steps (how far and how fast to take the next step) during the walking process based on the current states of the biped robot. Simulation results show that the obtained online walking motion is highly stable with large stability margin. In addition, the proposed algorithm is able to compensate for fairly large external disturbances affecting the walking robot.
URI: http://scholarbank.nus.edu.sg/handle/10635/33314
Appears in Collections:Ph.D Theses (Open)

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