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Abstract-This paper describes the new walk algorithm implemented on the NAO robot. NAO is a small fully actuated biped robot provided by the French company Aldebaran Robotics. Since the beginning of the company in July 2005, a major goal has been the development of robust walk for the robot. After 5 years of mecatronic design and improvements in robustness of the robot (7 prototypes) and multiple prototypes of humanoid dynamic walk algorithm, an omni-directional walk robust against small obstacles is now available for all the NAO units (more than 700) in the world.

The goal of this paper is to present a new realtime controller based on linear model predictive control for an omnidirectionnal wheeled humanoid robot. It is able to control both the mobile base of the robot and its body, while taking into account dynamical constraints. It makes it possible to have high velocity and acceleration motions by predicting the dynamic behavior of the robot in the future. Experimental results are proposed on the robot Pepper made by Aldebaran Robotics, showing good performance in terms of robustness and tracking control, efficiently managing kinematic and dynamical constraints.

This paper presents a numerical method to conceive and design the kinematic model of an anthropomorphic robotic hand used for gesturing and grasping. In literature, there are few numerical methods for the finger placement of human-inspired robotic hands. In particular, there are no numerical methods, for the thumb placement, that aim to improve the hand dexterity and grasping capabilities by keeping the hand design close to the human one. While existing models are usually the result of successive parameter adjustments, the proposed method determines the fingers placements by mean of empirical tests. Moreover, a surgery test and the workspace analysis of the whole hand are used to find the best thumb position and orientation according to the hand kinematics and structure. The result is validated through simulation where it is checked that the hand looks well balanced and that it meets our constraints and needs. The presented method provides a numerical tool which allows the easy computation of finger and thumb geometries and base placements for a human-like dexterous robotic hand.

This paper presents a novel design of a compact and light-weight robotic hand for a social humanoid robot. The proposed system is able to perform common hand gestures and self-adaptable grasps by mixing under-actuated and selfadaptable hand kinematics in a unique design. The hand answers the need for precise finger postures and sensor-less force feedback during gestures and for finger adaptation and autonomous force distribution during grasps. These are provided by a dual actuation system embodied within the palm and the fingers. Coexistence is ensured by compliant transmissions based on elastomer bars rather than classical tension springs, thanks to their high elastic coefficient at reduced sizes and strains. The proposed solution significantly reduces the weight and the size of the hand by using a reduced number of small actuators for gesturing and a single motor for grasping. The hand prototype (ALPHA) is realized to confirm the design feasibility and functional capabilities. It is controlled to provide safe human-robot interaction and preserve mechanical integrity in order to be embodied on a humanoid robot.