4 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…
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…
Symbolic Planning and Multi-Agent Path Finding in Extremely Dense Environments with Unassigned Agents
Bo Fu, Zhe Chen, Rahul Chandan +4
We introduce the Block Rearrangement Problem (BRaP), a challenging component of large warehouse management which involves rearranging storage blocks within dense grids to achieve a…
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…