Bio-Inspired and Energy-Efficient Convex Model Predictive Control for a Quadruped Robot

EasyChair Preprint 8540

Abstract

Animal running has been studied for a long time, but until now robots cannot repeat the same movements with energy efficiency close to animals. There are many controllers for controlling the movement of four-legged robots. The most popular is the Convex MPC. This paper presents a bioinspirational approach to increasing the energy efficiency of the state-of-theart Convex MPC controller. This approach is to set a reference trajectory for the Convex MPC in the form of a SLIP model. This model describes the movements of animals when running. Adding a SLIP trajectory increases the energy efficiency of the Pronk gait by 15 percent at a speed of 1 m/s.

Keyphrases: Bioinspiration, Model Predictive Control, Quadruped, energy efficiency

@booklet{EasyChair:8540,
  author    = {Aleksei Shamraev and Sergey Kolyubin},
  title     = {Bio-Inspired and Energy-Efficient Convex Model Predictive Control for a Quadruped Robot},
  howpublished = {EasyChair Preprint 8540},
  year      = {EasyChair, 2022}}