Motion Analysis by Proper Orthogonal Decomposition: an Application to the Gait Motion of the Humanoid Robot Lola

EasyChair Preprint 13420, version 1

Abstract

Autonomous bipedal robot locomotion is a challenging task because it requires stable, robust, and highly dynamic walking. Although our humanoid robot LOLA is capable of stable and robust walking in uncertain environments, its motion is far from being highly dynamic. A precise analysis of its walking motion is required to better understand the underlying gait pattern and to enhance the robot's soft- and hardware capabilities to achieve a highly dynamic gait. In this talk, we present an approach to compute and analyze the underlying fundamental gait pattern of LOLA using Proper Orthogonal Decomposition (POD). Human gait serves as an ideal model for walking robots, and thus a comparison with the basic human gait pattern is performed based on our POD-based gait characterization.

Keyphrases: Bipedal Locomotion, Humanoid Robots, Proper Orthogonal Decomposition, gait analysis

@booklet{EasyChair:13420,
  author    = {Arian Kist and Daniel Rixen},
  title     = {Motion Analysis by Proper Orthogonal Decomposition: an Application to the Gait Motion of the Humanoid Robot Lola},
  howpublished = {EasyChair Preprint 13420},
  year      = {EasyChair, 2024}}