Review of Autonomous Mobile Robots for the Warehouse Environment
Russell Keith, Hung Manh La
TL;DR
The paper addresses waste and inefficiency in warehouse material handling by examining autonomous mobile robots (AMRs) that navigate without fixed infrastructure. It synthesizes advances across hardware (sensors, edge processors, batteries), robotic control (localization, AI, path planning), and system control (resource management, scheduling, human-robot collaboration, and layout design). Key contributions include mapping localization and planning methods to real-world deployment, comparing centralized and decentralized scheduling, and evaluating human-robot collaboration strategies. The review identifies gaps in robustness, dynamic zoning, heterogeneous fleets, and human factors, providing a roadmap to guide future research and industry adoption of AMRs in large-scale warehouses.
Abstract
Autonomous mobile robots (AMRs) have been a rapidly expanding research topic for the past decade. Unlike their counterpart, the automated guided vehicle (AGV), AMRs can make decisions and do not need any previously installed infrastructure to navigate. Recent technological developments in hardware and software have made them more feasible, especially in warehouse environments. Traditionally, most wasted warehouse expenses come from the logistics of moving material from one point to another, and is exhaustive for humans to continuously walk those distances while carrying a load. Here, AMRs can help by working with humans to cut down the time and effort of these repetitive tasks, improving performance and reducing the fatigue of their human collaborators. This literature review covers the recent developments in AMR technology including hardware, robotic control, and system control. This paper also discusses examples of current AMR producers, their robots, and the software that is used to control them. We conclude with future research topics and where we see AMRs developing in the warehouse environment.