Online Payload Identification for Quadruped Robots (IROS'17)
Online Payload Identification for Quadruped Robots
G. Tournois, M. Focchi, A. del Prete, R. Orsolino, D. G. Caldwell and C. Semini
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'17)
The identification of inertial parameters is crucial to achieve high-performance
model-based control of legged robots.
The inertial parameters of the legs are typically not altered during
expeditions and therefore are best identified \textit{offline}.
On the other hand, the trunk parameters depend on the
modules mounted on the robot, like a
motor to provide the hydraulic power, or different sets of cameras for perception.
This motivates the use of recursive
approaches to identify \textit{online} mass and the position of the Center of Mass (CoM)
of the robot trunk, when a payload change occurs.
We propose two such approaches and analyze their robustness in simulation.
Furthermore, experimental trials on our 80-kg quadruped robot HyQ
show the applicability of our strategies during locomotion
to cope with large payload changes that would otherwise severely
compromise the balance of the robot.
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