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Found 7 papers, 4 papers with code
Terraforming -- Environment Manipulation during Disruptions for Multi-Agent Pickup and Delivery
In automated warehouses, teams of mobile robots fulfill the packaging process by transferring inventory pods to designated workstations while navigating narrow aisles formed by tightly packed pods.
Multi-Agent Terraforming: Efficient Multi-Agent Path Finding via Environment Manipulation
Multi-agent pathfinding (MAPF) is concerned with planning collision-free paths for a team of agents from their start to goal locations in an environment cluttered with obstacles.
Leveraging Experience in Lifelong Multi-Agent Pathfinding
Therefore, a solution to one query informs the next query, which leads to similarity with respect to the agents' start and goal positions, and how collisions need to be resolved from one query to the next.
Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks
The second stage solves only for drones, by routing them over a composite of the road network and the transit network defined by truck paths from the first stage.
Balancing Fairness and Efficiency in Traffic Routing via Interpolated Traffic Assignment
To address the inherent unfairness of SO routing, we study the ${\beta}$-fair SO problem whose goal is to minimize the total travel time while guaranteeing a ${\beta\geq 1}$ level of unfairness, which specifies the maximum possible ratio between the travel times of different users with shared origins and destinations.
Complexity of Planning
This is a chapter in the Encyclopedia of Robotics.
Robotics Computational Geometry Data Structures and Algorithms
Efficient Large-Scale Multi-Drone Delivery Using Transit Networks
Our results show that the framework computes solutions typically within a few seconds on commodity hardware, and that drones travel up to $360 \%$ of their flight range with public transit.
