Gabriele Nava

Stability analysis and design of momentum-based controllers for humanoid robots

Envisioned applications for humanoid robots call for the design of balancing and walking controllers. While promising results have been recently achieved, robust and reliable controllers are still a challenge for the control community dealing with humanoid robotics. Momentum-based strategies have proven their effectiveness for controlling humanoids balancing, but the stability analysis of these controllers is still missing. The contribution of this paper is twofold. First, we numerically show that the application of state-of-the-art momentum-based control strategies may lead to unstable zero dynamics. Secondly, we propose simple modifications to the control architecture that avoid instabilities at the zero-dynamics level. Asymptotic stability of the closed loop system is shown by means of a Lyapunov analysis on the linearized systems joint space. The theoretical results are validated with both simulations and experiments on the iCub humanoid robot.

Automatic gain tuning of a momentum based balancing controller for humanoid robots

This paper proposes a technique for automatic gain tuning of a momentum based balancing controller for humanoid robots. The controller ensures the stabilization of the centroidal dynamics and the associated zero dynamics. Then, the closed-loop, constrained joint space dynamics is linearized and the controllers gains are chosen so as to obtain desired properties of the linearized system. Symmetry and positive definiteness constraints of gain matrices are enforced by proposing a tracker for symmetric positive definite matrices. Simulation results are carried out on the humanoid robot iCub.

The CoDyCo Project Achievements and Beyond: Toward Human Aware Whole-Body Controllers for Physical Human Robot Interaction

The success of robots in real-world environments is largely dependent on their ability to interact with both humans and said environment. The FP7 EU project CoDyCo focused on the latter of these two challenges by exploiting both rigid and compliant contacts dynamics in the robot control problem. Regarding the former, to properly manage interaction dynamics on the robot control side, an estimation of the human behaviors and intentions is necessary. In this letter, we present the building blocks of such a human-in-the-loop controller, and validate them in both simulation and on the iCub humanoid robot using a human–robot interaction scenario. In this scenario, a human assists the robot in standing up from being seated on a bench.