  Perception is necessary for autonomous navigation in an unknown area crowded
with obstacles. It's challenging for a robot to navigate safely without any
sensors that can sense the environment, resulting in a $\textit{blind}$ robot,
and becomes more difficult when comes to a group of robots. However, it could
be costly to equip all robots with expensive perception or SLAM systems. In
this paper, we propose a novel system named $\textbf{ColAG}$, to solve the
problem of autonomous navigation for a group of $\textit{blind}$ UGVs by
introducing cooperation with one UAV, which is the only robot that has full
perception capabilities in the group. The UAV uses SLAM for its odometry and
mapping while sharing this information with UGVs via limited relative pose
estimation. The UGVs plan their trajectories in the received map and predict
possible failures caused by the uncertainty of its wheel odometry and unknown
risky areas. The UAV dynamically schedules waypoints to prevent UGVs from
collisions, formulated as a Vehicle Routing Problem with Time Windows to
optimize the UAV's trajectories and minimize time when UGVs have to wait to
guarantee safety. We validate our system through extensive simulation with up
to 7 UGVs and real-world experiments with 3 UGVs.
