Abstract
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.
Highlights
INTRODUCTIONRecent improvements in mobile robotics indicate that it is possible to achieve autonomous inspection and maintenance of critical industrial infrastructure in extreme environments (e.g., off-shore plants and nuclear sites) within the decade
Recent improvements in mobile robotics indicate that it is possible to achieve autonomous inspection and maintenance of critical industrial infrastructure in extreme environments within the decade
We present the projected inverse-dynamics to deal with constrained dynamics, which we will use to derive our locomotion controller for quadruped robots
Summary
Recent improvements in mobile robotics indicate that it is possible to achieve autonomous inspection and maintenance of critical industrial infrastructure in extreme environments (e.g., off-shore plants and nuclear sites) within the decade. The main benefit of the optimization-based control is the integration of the operational space tasks and the joint space dynamics in a single problem. Joint torques are the decision variables for the proposed control technique in this paper, and only one QP needs to be solved. For optimization-based approaches, operational tasks are bounded to joint space dynamics by optimization constraints. Tuning parameters, such as impedance gains require several trials. A seminal control technique called operational space control (OSC), presented first in Khatib (1987), provides us with the analytical solution to derive joint torques from desired operational tasks. Analytical Cartesian impedance control, based on the orthogonal projected inverse-dynamics, which allows us to analyze a legged robot using a mass-spring-damper model against disturbances. The proposed pipeline and controller are extensively validated on the torque controllable quadruped robot ANYmal (see Figure 1) in various scenarios
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