A simple control algorithm for controlling biped dynamic walking with stopping ability based on the footed inverted pendulum model

Abstract

In biped walking, dynamic balance ability is an important evaluation index. Zero-moment-point-based trajectory control is a common method for biped dynamic walking, but it requires complex control mechanisms that limit its applications. With the help of passive dynamics, the biped walking based on the inverted pendulum model can achieve dynamic walking in a simple way; however, it has no stopping ability, which is necessary for practical use. To solve this problem, this article proposes a footed inverted pendulum model and develops a simple three-part decomposition control algorithm for controlling biped dynamic walking based on the model. In the control algorithm, the biped walking is decomposed into three separate control parts: body posture, body height, and body velocity. Body posture is controlled by the stance hip, body height is controlled by the stance knee, and body velocity is controlled by the stance ankle and swing foot placement simultaneously. A simulation is presented to analyze the foot's effect on the inverted pendulum model. Two hardware experiments exploring velocity control and balance are described, with the results showing that the biped can achieve dynamic walking with stopping ability by using the simple control algorithm based on the footed inverted pendulum model.

State-Space Characterization of Balance Capabilities in Biped Systems with Segmented Feet

“…An equivalent reduced-order model of the proposed biped system is formulated to compare the balance capabilities of point-mass vs. multi-mass models. The biped standing posture is modeled with a footed LIP (Dafarra et al, 2016;Wang et al, 2016), which has a point mass representing the system's COM and a massless, rigid triangular foot with finite length and height (Figure 1; right). The dynamics of the LIP is linear due to the small angle approximation of the inverted pendulum and the imposed condition that the foot always remains in fixed flat contact with the ground (i.e., mode 1).…”

Implementation and Integration of Fuzzy Algorithms for Descending Stair of KMEI Humanoid Robot

“…To acquire a dynamic system of the humanoid robot, we use the simplification of the seven-links humanoid robot using Lagrange's method [23], process of developing a dynamic model for KMEI humanoid robot. Lagrange equation is the simple one of derivative equation from position and velocity.…”