An Optimization-Based Locomotion Controller for Quadruped Robots Leveraging Cartesian Impedance Control

Guiyang Xin, Wouter Wolfslag, Hsiu-Chin Lin, Carlo Tiseo, Michael Mistry

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Quadruped robots require compliance to handle unexpected external forces, such as impulsive contact forces from rough terrain, or from physical human-robot interaction. This paper presents a locomotion controller using Cartesian impedance control to coordinate tracking performance and desired compliance, along with Quadratic Programming (QP) to satisfy friction cone constraints, unilateral constraints, and torque limits. First, we resort to projected inverse-dynamics to derive an analytical control law of Cartesian impedance control for constrained and underactuated systems (typically a quadruped robot). Second, we formulate a QP to compute the optimal torques that are as close as possible to the desired values resulting from Cartesian impedance control while satisfying all of the physical constraints. When the desired motion torques lead to violation of physical constraints, the QP will result in a trade-off solution that sacrifices motion performance to ensure physical constraints. The proposed algorithm gives us more insight into the system that benefits from an analytical derivation and more efficient computation compared to hierarchical QP (HQP) controllers that typically require a solution of three QPs or more. Experiments applied on the ANYmal robot with various challenging terrains show the efficiency and performance of our controller.
Original languageEnglish
Article number48
Number of pages12
JournalFrontiers in Robotics and AI
Publication statusPublished - 24 Apr 2020

Keywords / Materials (for Non-textual outputs)

  • locomotion controller
  • projected inverse-dynamics
  • quadratic programming
  • impedance control
  • quadruped robots


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