Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision
  Avoidance   Robust motion planning is a well-studied problem in the robotics literature,
yet current algorithms struggle to operate scalably and safely in the presence
of other moving agents, such as humans. This paper introduces a novel framework
for robot navigation that accounts for high-order system dynamics and maintains
safety in the presence of external disturbances, other robots, and
non-deterministic intentional agents. Our approach precomputes a tracking error
margin for each robot, generates confidence-aware human motion predictions, and
coordinates multiple robots with a sequential priority ordering, effectively
enabling scalable safe trajectory planning and execution. We demonstrate our
approach in hardware with two robots and two humans. We also showcase our
work's scalability in a larger simulation.

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The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-lat
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The categories of this paper are: acc-phys
3
The categories of this paper are: physics
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The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
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The categories of this paper are: plasm-ph
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The categories of this paper are: q-fin
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The categories of this paper are: atom-ph
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The categories of this paper are: funct-an
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The categories of this paper are: comp-gas
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The categories of this paper are: econ
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg