2018/05/15 by Kendeas Theofanous, Theofanous, Kendeas
Computer Science · Engineering · #Artificial intelligence #Bipedalism #Computer science #Control (management) #Control engineering #Control theory (sociology) #Dynamic balance #Engineering #FOS: Computer and information sciences #Function (biology) #Gait #Inverted pendulum #Legged robot #Nonlinear system #Pendulum #Process (computing) #Prosthetics and Rehabilitation Robotics #Reinforcement learning #Robot #Robotic Locomotion and Control #Robotic Mechanisms and Dynamics #Robotics (cs.RO) #Simulation #Task (project management) #cs.RO
paper · pdf · doi:10.48550/arxiv.1805.05980
published in arXiv (Cornell University) (Cornell University)
arxiv created 2018/05/15 · openalex publication_date 2018/05/15 · arxiv updated 2018/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Locomotion of legged machines faces the problems of model complexity and computational costs. Algorithms based on complex models and/or reinforcement learning exist to solve the walking control task. In this project, we aim to develop a bipedal walking control system based on a simple model the Linear Inverted Pendulum model. In order to simplify the complex process of controlling legged locomotion, we make use of the technique of splitting the control into three parts as height control, forward velocity control and balance control. The forward velocity of the body has a linear relationship with the foot placement, therefore we use a linear function to realise foot placement. Our control system achieves stable walking gait in a simulated environment, where our bipedal robot walks more than 200 steps with a cyclic pattern in a stable, dynamic and almost natural manner. The experimental data are presented and analysed.