We present a differentiable pipeline for simulating the motion of objects that represent their
geometry as a continuous density field parameterized as a deep network. This includes …

The empirical success of derivative-free methods in reinforcement learning for planning
through contact seems at odds with the perceived fragility of classical gradient-based …

Robots must make and break contact with the environment to perform useful tasks, but
planning and control through contact remains a formidable challenge. In this work, we …

We present Dojo, a differentiable physics engine for robotics that prioritizes stable
simulation, accurate contact physics, and differentiability with respect to states, actions, and …

In this article, we present a convex formulation of compliant frictional contact and a robust
performant method to solve it in practice. By analytically eliminating contact constraints, we …

The force modulation of robotic manipulators has been extensively studied for several
decades. However, it is not yet commonly used in safety-critical applications due to a lack of …

Pressure Field Contact (PFC) was recently introduced as a method for detailed modeling of
contact interface regions at rates much faster than elasticity-theory models, while at the …

For both humans and robots, the sense of touch, known as tactile sensing, is critical for
performing contact-rich manipulation tasks. Three key challenges in robotic tactile sensing …

Contact-implicit trajectory optimization offers an appealing method of automatically
generating complex and contact-rich behaviors for robot manipulation and locomotion. The …

Ojhung is one of the indigenous Indonesian cultures from Sumenep Regency which
contains relevant science concepts to be applied in science learning. Therefore, this …