Multi-agent pathfinding (MAPF) is a well-studied abstract model for navigation in a multi-
robot system, where every robot finds the path to its goal position without any collision. Due …

The multi-agent pathfinding problem (MAPF) is the fundamental problem of planning paths
for multiple agents, where the key constraint is that the agents will be able to follow these …

In the field of mobile robotics, the study of multi-robot systems (MRSs) has grown
significantly in size and importance in recent years. Having made great progress in the …

Planning optimal paths for large numbers of robots is computationally expensive. In this
paper, we introduce a new framework for multirobot path planning called subdimensional …

In this paper, we consider the problem of concurrent assignment and planning of trajectories
(which we denote Capt) for a team of robots. This problem involves simultaneously …

We present a sampling-based framework for multi-robot motion planning. which combines
an implicit representation of roadmaps for multi-robot motion planning with a novel approach …

Rearranging multiple objects is a critical skill for robots so that they can effectively deal with
clutter in human spaces. This is a challenging problem as it involves combinatorially large …

Abstract This paper presents Goal Assignment and Planning: a computationally tractable,
complete algorithm for generating dynamically feasible trajectories for NN interchangeable …

The benefits of multi-robot systems are substantial, bringing gains in efficiency, quality, and
cost, and they are useful in a wide range of environments from warehouse automation, to …

This paper studies the underlying combinatorial structure of a class of object rearrangement
problems, which appear frequently in applications. The problems involve multiple, similar …