Dynamic Zoning of Industrial Environments with Autonomous Mobile Robots

TL;DR

This paper introduces a decentralized dynamic zoning algorithm for autonomous mobile robots in industrial environments, improving task distribution and reducing travel distance variability, thereby enhancing operational stability and maintenance planning.

Contribution

The paper proposes a novel decentralized dynamic zoning (DDZ) algorithm that adapts zones over time, avoiding single-point failure and improving task distribution among AMRs.

Findings

DDZ achieves a 68.7% reduction in travel distance standard deviation.

DDZ provides a more balanced task distribution compared to previous algorithms.

Initial results indicate lower throughput but better task sharing with DDZ.

Abstract

This paper presents a scheduling algorithm that divides a manufacturing/warehouse floor into zones that an Autonomous Mobile Robot (AMR) will occupy and complete part pick-up and drop-off tasks. Each zone is balanced so that each AMR will share each task equally. These zones change over time to accommodate fluctuations in production and to avoid overloading an AMR with tasks. A decentralized dynamic zoning (DDZ) algorithm is introduced to find the optimal zone design, eliminating the possibility of single-point failure from a centralized unit. Then a simulation is built comparing the adaptability of DDZ and other dynamic zoning algorithms from previous works. Initial results show that DDZ has a much lower throughput than other dynamic zoning algorithms but DDZ can achieve a better distribution of tasks. Initial results show that DDZ had a lower standard deviation of AMR total travel distance which was 2874.7 feet less than previous works. This 68.7\% decrease in standard deviation suggests that AMRs under DDZ travel a similar distance during production. This could be useful for real-world applications by making it easier to design charging and maintenance schedules without much downtime. Video demonstration of the system working can be seen here: \url{https://youtu.be/yVi026oVD7U}