We describe a method for multirobot trajectory planning in known, obstacle-rich environments.
We demonstrate our approach on a quadrotor swarm navigating in a warehouse setting. …

We define a system architecture for a large swarm of miniature quadcopters flying in dense
formation indoors. The large number of small vehicles motivates novel design choices for …

Multi-Agent Path Finding (MAPF) is well studied in both AI and robotics. Given a discretized
environment and agents with assigned start and goal locations, MAPF solvers from AI find …

Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical
computer science and operations research. We discuss issues that arise when generalizing …

We present Neural-Swarm2 , a learning-based method for motion planning and control that
allows heterogeneous multirotors in a swarm to safely fly in close proximity. Such operation …

We describe a method for formation-change trajectory planning for large quadrotor teams in
obstacle-rich environments. Our method decomposes the planning problem into two stages: …

The particle-in-cell (PIC) algorithm is one of the most widely used algorithms in computational
plasma physics. With the advent of graphical processing units (GPUs), large-scale plasma …

We consider a variant of the Multi-Agent Path-Finding problem that seeks both task assignments
and collision-free paths for a set of agents navigating on a graph, while minimizing the …

The authors present an overview of a hierarchical framework for coordinating task- and
motion-level operations in multirobot systems. Their framework is based on the idea of using …

Multi-agent path finding (MAPF) is a well-studied problem in artificial intelligence that can
be solved quickly in practice when using simplified agent assumptions. However, real-world …