  We consider a novel problem where multiple rigid convex polygonal objects
rest in randomly placed positions and orientations on a planar surface visible
from an overhead camera. The objective is to efficiently grasp and transport
all objects into a bin using multi-object push-grasps, where multiple objects
are pushed together to facilitate multi-object grasping. We provide necessary
conditions for frictionless multi-object push-grasps and apply these to filter
inadmissible grasps in a novel multi-object grasp planner. We find that our
planner is 19 times faster than a Mujoco simulator baseline. We also propose a
picking algorithm that uses both single- and multi-object grasps to pick
objects. In physical grasping experiments comparing performance with a
single-object picking baseline, we find that the frictionless multi-object
grasping system achieves 13.6\% higher grasp success and is 59.9\% faster, from
212 PPH to 340 PPH. See
\url{https://sites.google.com/view/multi-object-grasping} for videos and code.
