Edinburgh Research Explorer

Model Predictive Control for Motion Planning of Quadrupedal Locomotion

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Yapeng Shi
  • Pengfei Wang
  • Mantian Li
  • Xin Wang
  • Zhenyu Jiang
  • Zhibin Li

Related Edinburgh Organisations

Original languageEnglish
Title of host publication2019 International Conference on Advanced Robotics and Mechatronics (ICARM)
Number of pages6
StateAccepted/In press - 1 May 2019
EventIEEE International Conference on Advanced Robotics and Mechatronics (ICARM) - Osaka, Japan
Duration: 3 Jul 20195 Jul 2019
http://www.ieee-arm.org/

Conference

ConferenceIEEE International Conference on Advanced Robotics and Mechatronics (ICARM)
Abbreviated titleICARM 2019
CountryJapan
CityOsaka
Period3/07/195/07/19
Internet address

Abstract

This paper is motivated to transfer the model predictive control approach used in bipedal locomotion to formulate gait planning of quadrupedal robots. The particular lateral-sequence gait of quadrupeds is treated as an equivalence to the bipedal walking. The Model Predictive Control (MPC) algorithm uses 3D-Linear Inverted Pendulum Model for representing the center of mass dynamics for planning the quadrupedal gaits, and a dimensionless discretetime state-space formulated is derived for MPC. Subsequently, the footholds can be generated automatically via optimization of quadratic programming (QP) without the need of a separate footstep planner. The generated walking gaits were implemented and validated first in the physics simulation of a quadruped named EHbot, and then the effectiveness of the proposed method was further
demonstrated through our experiments. Both simulation and experimental data are presented and analyzed for evaluating the performance.

Event

ID: 88870305