LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Adaptive optimal output regulation for wheel-legged robot Ollie: A data-driven approach

Photo from wikipedia

The dynamics of a robot may vary during operation due to both internal and external factors, such as non-ideal motor characteristics and unmodeled loads, which would lead to control performance… Click to show full abstract

The dynamics of a robot may vary during operation due to both internal and external factors, such as non-ideal motor characteristics and unmodeled loads, which would lead to control performance deterioration and even instability. In this paper, the adaptive optimal output regulation (AOOR)-based controller is designed for the wheel-legged robot Ollie to deal with the possible model uncertainties and disturbances in a data-driven approach. We test the AOOR-based controller by forcing the robot to stand still, which is a conventional index to judge the balance controller for two-wheel robots. By online training with small data, the resultant AOOR achieves the optimality of the control performance and stabilizes the robot within a small displacement in rich experiments with different working conditions. Finally, the robot further balances a rolling cylindrical bottle on its top with the balance control using the AOOR, but it fails with the initial controller. Experimental results demonstrate that the AOOR-based controller shows the effectiveness and high robustness with model uncertainties and external disturbances.

Keywords: output regulation; controller; wheel; adaptive optimal; optimal output; wheel legged

Journal Title: Frontiers in Neurorobotics
Year Published: 2023

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.