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Viable Multi-Contact Posture Computation for Humanoid Robots using Nonlinear Optimization on Manifolds

Abstract : Humanoid robots are complex poly-articulated structures whose kinematics and dynamics are governed by nonlinear equations. Finding viable postures to realize set-point task objectives under a set of constraints (intrinsic and extrinsic limitations) is a key issue in the planning of robot motion and an important feature of any robotics framework. It is handled by the so called posture generator (PG) that consists in formalizing the viable posture as the solution to a nonlinear optimization problem. We present several extensions to the state-of-the-art by exploring new formulations and resolution methods for the posture generation problems. We reformulate the notion of contact constraints by adding variables to enrich our optimization problem and allow the solver to decide on the shape of the intersection of contact polygons or of the location of a contact point on a non-flat surface. We present a reformulation of the PG problem that encompasses non-Euclidean manifolds natively for a more elegant and efficient mathematical formulation of the problems. To solve such problems, we decided to implement a new SQP solver that is most suited to non-Euclidean manifolds structural objects. By doing so, we have a better mastering in the way to tune and specialize our solver for robotics problems.
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Stanislas Brossette. Viable Multi-Contact Posture Computation for Humanoid Robots using Nonlinear Optimization on Manifolds. Robotics [cs.RO]. Université Montpellier, 2016. English. ⟨NNT : 2016MONTT295⟩. ⟨tel-01816943⟩

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