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 …

Abstract Purpose of Review Planning collision-free paths for multiple robots is important for
real-world multi-robot systems and has been studied as an optimization problem on graphs …

The multi-agent path-finding (MAPF) problem has recently received a lot of attention.
However, it does not capture important characteristics of many real-world domains, such as …

We study prioritized planning for Multi-Agent Path Finding (MAPF). Existing prioritized MAPF
algorithms depend on rule-of-thumb heuristics and random assignment to determine a fixed …

We study the offline Multi-Agent Pickup-and-Delivery (MAPD) problem, where a team of
agents has to execute a batch of tasks with release times in a known environment. To …

In the multi-agent path finding (MAPF) the task is to find non-conflicting paths for multiple
agents. In this paper we present the first SAT-solver for the sum-of-costs variant of MAPF …

We study the TAPF (combined target-assignment and path-finding) problem for teams of
agents in known terrain, which generalizes both the anonymous and non-anonymous multi …

Abstract 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 …

Speed is essential in wildlife surveys due to the dynamic movement of animals throughout
their environment and potentially extreme changes in weather. In this work, we present a …

Abstract The Multi-Agent Pickup and Delivery (MAPD) problem models applications where a
large number of agents attend to a stream of incoming pickup-and-delivery tasks. Token …