@InProceedings{wang:rss:2019,
  author    = {Wang, Yuquan and Kheddar, Abderrahmane},
  title     = {Impact-friendly robust control design with task-space quadratic optimization},
  booktitle = {Robotics: Science and Systems},
  year      = {2019},
  address   = {Freiburg im Breisgau, Germany},
  month     = {June 22-June 26},
  url       = {http://www.roboticsproceedings.org/rss15/p32.pdf},
  keywords  = {robot control, quadratic programming, impact control, task-space control, physical interaction},
  doi       = {10.15607/RSS.2019.XV.032},
  abstract  = {Almost all known robots fear impacts. Unlike humans, robots keep guarded motions to near zero-velocity prior to establishing contacts with their surroundings. This significantly slows down robotic tasks involving physical interaction. Two main ingredients are necessary to remedy this limitation: impactfriendly hardware design, and impact-friendly controllers. Our work focuses on the controller aspect. Task-space controllers formulated as quadratic programming (QP) are widely used in roboticstogeneratemodularandreactivemotionforalargerange of task specifications under various constraints. We explicitly introduce discrete impact dynamics model into the QP-based controllers to generate robot motions that are robust to impactinduced state jumps in the joint velocities and joint torques. Our simulations, validate that our proposed impact-friendly QP controller is robust to contact impacts, shall they be expected or not.Therefore,wecanexploititforestablishingcontactswithhigh velocities, and explicitly generate task-purpose impulsive forces.}
}