International audienceA crucial part in biped walking motion generation is to ensure dynamic feasibility, which takes the form of a nonlinear constraint in the general case. Our proposition is to bound the nonlinear part of the dynamic feasibility constraint between some properly chosen extreme values. Making sure that this constraint is satisfied for the extreme values guarantees its satisfaction for all possible values in between. This follows a classical approach from robust nonlinear control theory, which is to consider a nonlinear dynamical system as a specific selection of a time-invariant Linear Differential Inclusion. As a result, dynamic feasibility can be imposed by using only linear constraints, which can be included in an efficient linear MPC scheme, to generate 3D walking motions online. Our simulation results show two major achievements: 1) walking motions over uneven ground such as stairs can be generated online, with guaranteed kinematic and dynamic feasibility, 2) walking on flat ground is significantly improved, with a 3D motion of the CoM closely resembling the one observed in humans

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.

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While realizing a task, human-beings are able to use grasping inside their environment in order to keep the most stable balance. Although such a behavior is quite natural for humans, it is very difficult to find the best formulation to adapt human motion to humanoid robots. This paper proposes a conceptually simple framework of human posture control based on optimization which takes into account grasp and friction and achieves robustness against external disturbances. A new stability criteria is also introduced.Contrary to most other approaches, our method deals not only with unilateral contacts with friction but also with bilateral grasps. This allows for arbitrarily pulling, pushing or twisting on a handhold. Additionally, and in contrast to classical methods based on ZMP, our method also accounts for contacts not being all in the same plane.