Model Predictive Control for Motion Planning of Quadrupedal Locomotion

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

doi:10.1109/ICARM.2019.8834241

Model Predictive Control for Motion Planning of Quadrupedal Locomotion

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	2019 IEEE 4th International Conference on Advanced Robotics and Mechatronics (ICARM)
Place of Publication	Toyonaka, Japan
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	87-92
Number of pages	6
ISBN (Electronic)	978-1-7281-0064-7
ISBN (Print)	978-1-7281-0065-4
DOIs	https://doi.org/10.1109/ICARM.2019.8834241
Publication status	Published - 12 Sep 2019
Event	IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) - Osaka, Japan Duration: 3 Jul 2019 → 5 Jul 2019 http://www.ieee-arm.org/

Conference

Conference	IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)
Abbreviated title	ICARM 2019
Country/Territory	Japan
City	Osaka
Period	3/07/19 → 5/07/19
Internet address	http://www.ieee-arm.org/

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Model Predictive Control_SHI_DoA010519_AFVAccepted author manuscript, 4.81 MB

https://ieeexplore.ieee.org/document/8834241Licence: All Rights Reserved

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@inproceedings{e9c523e1193e4928b0da7d1480565395,

title = "Model Predictive Control for Motion Planning of Quadrupedal Locomotion",

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.",

author = "Yapeng Shi and Pengfei Wang and Mantian Li and Xin Wang and Zhenyu Jiang and Zhibin Li",

year = "2019",

month = sep,

day = "12",

doi = "10.1109/ICARM.2019.8834241",

language = "English",

isbn = "978-1-7281-0065-4",

pages = "87--92",

booktitle = "2019 IEEE 4th International Conference on Advanced Robotics and Mechatronics (ICARM)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "IEEE International Conference on Advanced Robotics and Mechatronics (ICARM), ICARM 2019 ; Conference date: 03-07-2019 Through 05-07-2019",

url = "http://www.ieee-arm.org/",

}

Shi, Y, Wang, P, Li, M, Wang, X, Jiang, Z & Li, Z 2019, Model Predictive Control for Motion Planning of Quadrupedal Locomotion. in 2019 IEEE 4th International Conference on Advanced Robotics and Mechatronics (ICARM). Institute of Electrical and Electronics Engineers (IEEE), Toyonaka, Japan, pp. 87-92, IEEE International Conference on Advanced Robotics and Mechatronics (ICARM), Osaka, Japan, 3/07/19. https://doi.org/10.1109/ICARM.2019.8834241

Model Predictive Control for Motion Planning of Quadrupedal Locomotion. / Shi, Yapeng; Wang, Pengfei; Li, Mantian et al.

2019 IEEE 4th International Conference on Advanced Robotics and Mechatronics (ICARM). Toyonaka, Japan : Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 87-92.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Model Predictive Control for Motion Planning of Quadrupedal Locomotion

AU - Shi, Yapeng

AU - Wang, Pengfei

AU - Li, Mantian

AU - Wang, Xin

AU - Jiang, Zhenyu

AU - Li, Zhibin

PY - 2019/9/12

Y1 - 2019/9/12

N2 - 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.

AB - 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.

U2 - 10.1109/ICARM.2019.8834241

DO - 10.1109/ICARM.2019.8834241

M3 - Conference contribution

SN - 978-1-7281-0065-4

SP - 87

EP - 92

BT - 2019 IEEE 4th International Conference on Advanced Robotics and Mechatronics (ICARM)

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Toyonaka, Japan

T2 - IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

Y2 - 3 July 2019 through 5 July 2019

ER -

Model Predictive Control for Motion Planning of Quadrupedal Locomotion

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