Height varying humanoid robot walking through model predictive control
Autores
Proceedings 2019 Latin American Robotics Symposium 2019 Brazilian Symposium on Robotics and 2019 Workshop on Robotics in Education LARS Sbr Wre 2019 , pp. 49-54 , Article 9018627
Resumo
© 2019 IEEE.The present paper proposes the application of Model Predictive Control (MPC) to the bipedal walking problem. Classically, bipedal robots maintains constant height of the center of mass (CoM) during walking, since this constraint makes the underlying dynamical system linear. Nevertheless, researches show that vertical CoM motion is one of many mechanisms humans use to reduce energetic cost during walking. In this paper, we show that if the height is modified through a predefined function, the system becomes linear time-varying, which may be handled by MPC techniques. By means of simulations, the stability behavior of the robot is verified. Finally, a high-fidelity simulation model based on the Gazebo simulator is used to validate the energetic cost reduction due to the vertical CoM motion.
Palavras-chave
2-s2.0-85082167358