@InProceedings{samy:icra:2017,
  author    = {Samy, Vincent and Bouyarmane, Karim and Kheddar, Abderrahmane},
  title     = {QP-based Adaptive-Gains Compliance Control in Humanoid Falls},
  booktitle = {IEEE International Conference on Robotics and Automation},
  year      = {2017},
  pages     = {4762--4767},
  address   = {Singapore},
  month     = {May 29-June 2},
  url       = {https://hal.archives-ouvertes.fr/hal-01365108v2/document},
  keywords  = {Collision avoidance, Compliance control, Damping, Elasticity, Humanoid Robots, Impact (mechanical), Mechanical Contact, PD control, Quadratic progamming, Robot Dynamics, Torque},
  doi       = {10.1109/ICRA.2017.7989553},
  abstract  = {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 \textendash 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.}
}