Common methods for learning robot dynamics assume motion is continuous, causing
unrealistic model predictions for systems undergoing discontinuous impact and stiction …

So-called robot–object Lagrangian systems consist of a class of nonsmooth underactuated
complementarity Lagrangian systems, with a specific structure: an “object” and a “robot” …

We propose a control framework, which can utilize tactile information by exploiting the
complementarity structure of contact dynamics. Since many robotic tasks, like manipulation …

While many robotic tasks, like manipulation and locomotion, are fundamentally based in
making and breaking contact with the environment, state-of-the-art control policies struggle …

Physical reasoning is a core aspect of intelligence in animals and humans. A central
question is what model should be used as a basis for reasoning. Existing work considered …

This letter proposes a decoupled two-level model-based planning strategy and control for a
class of robotic tasks involving impact to be made with desired performance and constraints …

Motion planning for robotic manipulation makes heavy use of quasistatic models, but these
same models have not yet proven useful for simulation. This is because in many multi …

Complementarity problems, a class of mathematical optimization problems with
orthogonality constraints, are widely used in many robotics tasks, such as locomotion and …

Robotic manipulation and locomotion often entail nearly-simultaneous collisions—such as
heel and toe strikes during a foot step—with outcomes that are extremely sensitive to the …

We believe that the future of robot motion planning will look very different than how it looks
today: instead of complex collision avoidance trajectories with a brittle dependence on …