A common approach to the generation of walking patterns for humanoid robots consists in adopting a layered control architecture. This paper proposes an architecture composed of three nested control loops. The outer loop exploits a robot kinematic model to plan the footstep positions. In the mid layer, a predictive controller generates a Center of Mass trajectory according to the well-known table-cart model. Through a whole-body inverse kinematics algorithm, we can define joint references for position controlled walking. The outcomes of these two loops are then interpreted as inputs of a stack-of-task QP-based torque controller, which represents the inner loop of the presented control architecture. This resulting architecture allows the robot to walk also in torque control, guaranteeing higher level of compliance. Real world experiments have been carried on the humanoid robot iCub.

Abstract-This paper proposes control laws ensuring the stabilization of a time-varying desired joint trajectory and joint limit avoidance in the case of fully-actuated manipulators. The key idea is to perform a parametrization of the feasible joint space in terms of exogenous states. It follows that the control of these states allows for joint limit avoidance. One of the main outcomes of this paper is that position terms in control laws are replaced by parametrized terms. Stability and convergence of time-varying reference trajectories obtained with the proposed method are demonstrated to be in the sense of Lyapunov. The introduced control laws are verified by carrying out experiments on two degrees-of-freedom of the torque-controlled humanoid robot iCub.

Generating complex whole-body movements for humanoid robots is now most often achieved with multi-task whole-body controllers based on quadratic programming. To perform on the real robot, such controllers often require a human expert to tune or optimize the many parameters of the controller related to the tasks and to the specific robot, which is generally reported as a tedious and time consuming procedure. This problem can be tackled by automatically optimizing some parameters such as task priorities or task trajectories, while ensuring constraints satisfaction, through simulation. However, this does not guarantee that parameters optimized in simulation will also be optimal for the real robot. As a solution, the present paper focuses on optimizing task priorities in a robust way, by looking for solutions which achieve desired tasks under a variety of conditions and perturbations. This approach, which can be referred to as domain randomization, can greatly facilitate the transfer of optimized solutions from simulation to a real robot. The proposed method is demonstrated using a simulation of the humanoid robot iCub for a whole-body stepping task. This work was supported by the EU H2020 program under the Marie Sklodowska-Curie SECURE grant (n.642667), as well as the european projects An.Dy (n.731540) and Comanoid (n.645097).

The present paper is devoted to an experimental investigation of the cavity formed upon a single-drop impingement onto a traveling solitary surface wave on a deep pool of the same liquid. The dynamics of the cavity throughout its complete expansion and receding phase are analyzed using high-speed shadowgraphy and compared to the outcomes of drop impingements onto steady liquid surface films having equal thickness. The effects of the surface wave velocity, amplitude and phase, drop impingement velocity, and liquid viscosity on the cavity's diameter and depth evolution are accurately characterized at various time instants. The wave velocity induces a distinct and in time increasing inclination of the cavity in the wave propagation direction. In particular for strong waves an asymmetrical distribution of the radial expansion and retraction velocity along the cavity's circumference is observed. A linear dependency between the absolute Weber number and the typical length and time scales associated with the cavity's maximum depth and maximum diameter is reported.

TopOwl ® is an original concept of binocular Helmet Mounted Sight and Display system (HMSD) for helicopters, where two Image Intensifier Tubes (IIT) are integrated on the headgear and optically coupled to the clear visor placed in front of the pilot's eyes. Thales recently developed a new version of its TopOwl ® 's Display Module with the objective to have an HMSD capable to achieve all kind of missions up to the darkest night levels. The main enhancements are the redesign of the optical combination, the use of new optical materials and of latest generation of optical design tools. Two flyable prototypes of this new design were manufactured. A performance assessment has been conducted, showing a significant improvement of the night vision performances, reaching performances equivalent to those of last issued NVGs. These evaluations are being completed by different flight test evaluations.