Design of KAIST HOUND, a Quadruped Robot Platform for Fast and Efficient Locomotion with Mixed-Integer Nonlinear Optimization of a Gear Train

This paper introduces a design method for an efficient and agile quadruped robot. A mixed-integer optimization formulation including the number of gear teeth is derived to obtain the optimal gear ratio that minimizes cost for a running-trot with the target speed of 3 m/s. With the inclusion of integ...

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Bibliographic Details
Published in2022 International Conference on Robotics and Automation (ICRA) pp. 6614 - 6620
Main Authors Shin, Young-Ha, Hong, Seungwoo, Woo, Sangyoung, Choe, JongHun, Son, Harim, Kim, Gijeong, Kim, Joon-Ha, Lee, KangKyu, Hwangbo, Jemin, Park, Hae-Won
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.05.2022
Subjects
Automation
Costs
Design methodology
Gears
Heating systems
Legged locomotion
Predictive models
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Summary:This paper introduces a design method for an efficient and agile quadruped robot. A mixed-integer optimization formulation including the number of gear teeth is derived to obtain the optimal gear ratio that minimizes cost for a running-trot with the target speed of 3 m/s. With the inclusion of integer constraints related to the number of gear teeth, detailed design considerations of gear trains can be included in the optimization process. Thermal dissipation of the motor controller is also taken into account in the optimization to consider heat generation during high-speed running. KAIST Hound, a 45 kg robot, designed with the obtained design parameters has successfully demonstrated a 3 m/s running-trot using a nonlinear model predictive controller (NMPC). Furthermore, the robot has proved its robustness by the demonstration of additional experiments such as 22° slope climbing, 3.2 km walking, and traversing a 35 cm obstacle.
DOI:10.1109/ICRA46639.2022.9811755