  While there has been remarkable progress recently in the fields of
manipulation and locomotion, mobile manipulation remains a long-standing
challenge. Compared to locomotion or static manipulation, a mobile system must
make a diverse range of long-horizon tasks feasible in unstructured and dynamic
environments. While the applications are broad and interesting, there are a
plethora of challenges in developing these systems such as coordination between
the base and arm, reliance on onboard perception for perceiving and interacting
with the environment, and most importantly, simultaneously integrating all
these parts together. Prior works approach the problem using disentangled
modular skills for mobility and manipulation that are trivially tied together.
This causes several limitations such as compounding errors, delays in
decision-making, and no whole-body coordination. In this work, we present a
reactive mobile manipulation framework that uses an active visual system to
consciously perceive and react to its environment. Similar to how humans
leverage whole-body and hand-eye coordination, we develop a mobile manipulator
that exploits its ability to move and see, more specifically -- to move in
order to see and to see in order to move. This allows it to not only move
around and interact with its environment but also, choose "when" to perceive
"what" using an active visual system. We observe that such an agent learns to
navigate around complex cluttered scenarios while displaying agile whole-body
coordination using only ego-vision without needing to create environment maps.
Results visualizations and videos at https://spin-robot.github.io/
