QP-based Adaptive-Gains Compliance Control in Humanoid Falls

Vincent Samy (1) , Karim Bouyarmane (2) , Abderrahmane Kheddar (3)

1 LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 LARSEN - Lifelong Autonomy and interaction skills for Robots in a Sensing ENvironment
3 IDH - Interactive Digital Humans

We address the problem of humanoid falling with a decoupled strategy consisting of a pre-impact and a postimpact stage. In the pre-impact stage, geometrical reasoning allows the robot to choose appropriate impact points in the surrounding environment and to adopt a posture to reach them while avoiding impact-singularities and preparing for the postimpact. The surrounding environment can be unstructured and may contain cluttered obstacles. The post-impact stage uses a quadratic program controller that adapts on-line the joint proportional-derivative (PD) gains to make the robot compliant-to absorb impact and post-impact dynamics, which lowers possible damage risks. This is done by a new approach incorporating the stiffness and damping gains directly as decision variables in the QP along with the usually-considered variables of joint accelerations and contact forces. Constraints of the QP prevent the motors from reaching their torque limits during the fall. Several experiments on the humanoid robot HRP-4 in a full-dynamics simulator are presented and discussed.

Mots clés: Humanoid robot; Active compliance; Safe fall

Domaines: Automatique / Robotique

Vincent Samy, Karim Bouyarmane, Abderrahmane Kheddar. QP-based Adaptive-Gains Compliance Control in Humanoid Falls. ICRA: International Conference on Robotics and Automation, May 2017, Singapour, Singapore. pp.4762-4767, ⟨10.1109/ICRA.2017.7989553⟩. ⟨hal-01365108v2⟩