100 citations · 161 across the 9 of their papers we have counts for
10 papers
Model-Free Adaptive Parameter Tuning for Efficient Multi-Robot Warehouse Operations
Pratap Tokekar, Mouhacine Benosman, Rahul Chandan +3
Robotic Fulfillment Centers (FCs) store inventory on shelves (pods) arranged in dense blocks. Retrieving a target pod that is buried deep in a block requires moving obstructing pod…
Optimal and Scalable MAPF via Multi-Marginal Optimal Transport and Schrödinger Bridges
Usman A. Khan, Joseph W. Durham
We consider anonymous multi-agent path finding (MAPF) where a set of robots is tasked to travel to a set of targets on a finite, connected graph. We show that MAPF can be cast as a…
Multi-Objective Reinforcement Learning for Large-Scale Tote Allocation in Human-Robot Collaborative Fulfillment Centers
Sikata Sengupta, Guangyi Liu, Omer Gottesman +4
Optimizing the consolidation process in container-based fulfillment centers requires trading off competing objectives such as processing speed, resource usage, and space utilizatio…
Multi-robot Path Planning and Scheduling via Model Predictive Optimal Transport (MPC-OT)
Usman A. Khan, Mouhacine Benosman, Wenliang Liu +2
In this paper, we propose a novel methodology for path planning and scheduling for multi-robot navigation that is based on optimal transport theory and model predictive control. We…
DeepFleet: Multi-Agent Foundation Models for Mobile Robots
Ameya Agaskar, Sriram Siva, William Pickering +18
We introduce DeepFleet, a suite of foundation models designed to support coordination and planning for large-scale mobile robot fleets. These models are trained on fleet movement d…
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
Guangyi Liu, Suzan Iloglu, Michael Caldara +2
In Amazon robotic warehouses, the destination-to-chute mapping problem is crucial for efficient package sorting. Often, however, this problem is complicated by uncertain and dynami…
Lifelong Multi-Agent Path Finding in Large-Scale Warehouses
Jiaoyang Li, Andrew Tinka, Scott Kiesel +3
Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where ag…
The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Research
Jürgen Leitner, Adam W. Tow, Jake E. Dean +15
Robotic challenges like the Amazon Picking Challenge (APC) or the DARPA Challenges are an established and important way to drive scientific progress. They make research comparable…
Discrete Partitioning and Coverage Control for Gossiping Robots
Joseph W. Durham, Ruggero Carli, Paolo Frasca +1
We propose distributed algorithms to automatically deploy a team of mobile robots to partition and provide coverage of a non-convex environment. To handle arbitrary non-convex envi…
Pairwise Optimal Discrete Coverage Control for Gossiping Robots
Joseph W. Durham, Ruggero Carli, Francesco Bullo
We propose distributed algorithms to automatically deploy a group of robotic agents and provide coverage of a discretized environment represented by a graph. The classic Lloyd appr…