# Review of Autonomous Mobile Robots for the Warehouse Environment

arXiv: https://arxiv.org/abs/2406.08333 · HTML: https://mlsanity.com/paper/2406.08333/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jun 2024.

## Built on by (most cited first, 7 of 7)

- [Deep Meta Coordination Graphs for Multi-agent Reinforcement Learning](https://mlsanity.com/paper/2502.04028/) (2025)
- [CostNav: A Navigation Benchmark for Real-World Economic-Cost Evaluation of Physical AI Agents](https://mlsanity.com/paper/2511.20216/) (2025)
- [Action-Graph Policies: Learning Action Co-dependencies in Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2602.17009/) (2026)
- [A Novel Camera-to-Robot Calibration Method for Vision-Based Floor Measurements](https://mlsanity.com/paper/2603.15126/) (2026)
- [Safe Human Robot Navigation in Warehouse Scenario](https://mlsanity.com/paper/2503.21141/) (2025)
- [World Models for Autonomous Navigation of Terrestrial Robots from LIDAR Observations](https://mlsanity.com/paper/2512.03429/) (2025)
- [Do LLM-derived graph priors improve multi-agent coordination?](https://mlsanity.com/paper/2604.17191/) (2026)

## Abstract (arXiv)

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.