This article reviews the state-of-the-art modeling and control techniques for aerial robots
such as quadrotor systems and presents several future research directions in this area. The …

We present a novel model for Tracking Any Point (TAP) that effectively tracks any queried
point on any physical surface throughout a video sequence. Our approach employs two …

Visual model-based reinforcement learning (RL) has the potential to enable sample-efficient
robot learning from visual observations. Yet the current approaches typically train a single …

Generic motion understanding from video involves not only tracking objects, but also
perceiving how their surfaces deform and move. This information is useful to make …

Representing robotic manipulation tasks as constraints that associate the robot and the
environment is a promising way to encode desired robot behaviors. However, it remains …

Thin, reflective objects such as forks and whisks are common in our daily lives, but they are
particularly chal-lenging for robot perception because it is hard to reconstruct them using …

Robot manipulation of multiple objects is an important topic for applications including
warehouse automation, service robots performing cleaning, and large-scale object sorting …

While visual imitation learning offers one of the most effective ways of learning from visual
demonstrations, generalizing from them requires either hundreds of diverse demonstrations …

Humans have a strong intuitive understanding of the 3D environment around us. The mental
model of the physics in our brain applies to objects of different materials and enables us to …

We present a method to learn compositional multi-object dynamics models from image
observations based on implicit object encoders, Neural Radiance Fields (NeRFs), and …