MOV.AI disrupts Autonomous Mobile Robot development with a Robotics Engine Platform that contains everything needed to quickly build, deploy and operate intelligent robots.
Picture this: a warehouse facility where cart tuggers, picking robots, autonomous pallet movers, cleaning robots, and people all work side by side. This reality, which not too long ago was possible only in our imagination, exists in a growing number of facilities.
Autonomous Mobile Robots (AMRs) have made huge strides over the past few years and are a key element in warehouse automation efforts. According to Gartner, 96% of their supply chain survey respondents had invested or were planning to invest in robotics over the next two years. What’s more, 93% of the companies who have already introduced robots to their operations plan to expand their fleet sizes and introduce additional use cases.
Growing fleets and the variety of use cases have the potential to create chaos. Robot activities need to be orchestrated and synchronized both from a process and operational point of view. Different tasks need to be synchronized to ensure the continuity of business flows. Robot movement needs to be controlled and synchronized to avoid congestion or collisions.
To date, most AMR vendors offer some level of fleet management software that helps manage their robots. The problem is that these systems are mostly vendor-specific. To manage an increasingly diverse robot fleet there is a need for a system that can manage robots from multiple vendors in a shared space – a Heterogeneous Fleet Management System (HFMS), or Multi-Agent Orchestration Platforms as Gartner calls them.
Simply put, a Heterogeneous Fleet Management System ensures the efficient and continuous operation of multiple robots from different vendors in a shared space. It is the grand orchestrator that ensures business KPIs are met safely and efficiently.
Specifically, an effective HFMS contains a range of functionalities that ensure smooth fleet operation. Some of these tasks may seem straightforward or sound similar to vendor-specific Fleet Management Systems, but the difference is that they must apply to any robot type or make in the fleet – and there’s the rub!
Lack of heterogeneous fleet management can highly reduce efficiency. Task allocation and prioritization may be suboptimal, processes may not be synchronized end to end and uncoordinated use of shared resources may result in delays, deadlocks and unnecessary idle times. What’s more, the need to configure and operate multiple discrete systems creates employee overhead and increases the chance of errors. Heterogeneous Fleet Management systems improve efficiency, contribute to operational stability and continuity, allow customization, and ensure business agility.
Fleet status monitoring – Real-time dashboards, location tracking, alerts and notifications, logging, and health monitoring.
Fleet control – Basic commands for both individual AMRs and the fleet as a whole, task dispatching, and remote recovery.
Traffic management – Setup of standard traffic rules as well as conflict resolution strategies.
Tasks management – Task optimization, task queuing, and intelligent task assignment based on the fleet state.
External integrations with WMS, WES, WCS, ERP, and a variety of IIoT (Industrial Internet of Things) devices, such as doors, elevators, conveyors, scanning machines, sorting machines, and more. This integration should allow both the flow of information and control commands in real-time.
Vendor-agnostic setup and deployment – Enabling full definition of the environment, AMR onboarding, unified task definition, rules, etc. for all AMRs using a single pane of glass. Vendor-agnostic setup does not mean that you can set up each AMR separately in the same tool. It means that you can set up rules and infrastructure once and apply them to all AMRs. You can create compound tasks and check the setup on one AMR against the other for conflicts. It is a truly holistic setup.
Analytics and decision support systems – A holistic view of the ongoing fleet operation to drive continuous improvement.
HFMS are highly sophisticated systems that combine various technology types and approaches. While several systems have been introduced to the market, they widely differ in their ability to provide true heterogeneous fleet management. To help AMR operators and integrators better understand the differences between these solutions and the value they deliver, we suggest a four-level maturity model:
LEVEL 1 Foundational Fleet Awareness | LEVEL 2 Basic Control and Coordination | LEVEL 3 Intelligent Orchestration | LEVEL 4 Comprehensive Fleet Management |
|---|---|---|---|
Real-time location tracking, basic alerts, limited operational data logging, fundamental health monitoring. | Start/stop, pause/resume, trigger predefined tasks, remote AMR recovery.
| Traffic management, common management of shared resources such as IIoT devices, dynamic conflict resolution, integrated task management including real time task prioritization, queuing, and assignment.
| Vendor-agnostic deployment allowing for integrated set-up and process update from a single pane of glass.
Real-time AMR task and paths definition, regardless of make, for continuous efficiency optimization. |
The key challenge with Levels 1 and 2 lies in traffic management. Without any coordination between AMRs or with human-operated vehicles, the risk of deadlocks and collisions is high.
Level 3 partially addresses this with zone access control. These restricted zones create a stop-and-go system, similar to traffic lights, but it can be inefficient and limit overall flow, especially in dynamic environments.
Level 4 offers the most comprehensive solution. By integrating with the AMRs themselves, Level 4 allows for precise control of their movements and real-time traffic management. This facilitates a unified deployment and smoother overall operation.
For simplicity, we have created a comparison table of the degree of heterogeneity you can expect at each level. When evaluating solutions, refer to this table to understand the impact on your day-to-day operation.
Intuitive, user-friendly interfaces: Including interactive guides, automated processes, and error prevention.
Robust cybersecurity: Measures for secure communication, data encryption, and access control that address specific open, multi-vendor platform vulnerabilities and attack vectors.
Easy connection to third-party AMRs: Quick and hassle-free onboarding of new AMRs from new vendors, real-time two-way communication integration.
Currently, the market predominantly offers systems operating at Levels 1 and 2. Some Level 3 and 4 functionalities may exist, but are not vendor-neutral and do not offer true heterogeneous management.
This is expected to change over the next few years, as the demand from customers is there, with the growing need to efficiently operate multiple types of robots in shared spaces.
The development and consolidation of protocols that standardize communication between AMRs and fleet managers will become indispensable for efficient fleet management.
The growing complexity of warehouse automation, with diverse robots working alongside humans, necessitates Heterogeneous Fleet Management Systems (HFMS), that enable integrated deployment and operation of multi-function, multi-vendor AMR fleets.
In this article, MOV.AI proposes a maturity model for Heterogeneous Fleet Management Systems (HFMS) based on the level of integration they offer. We hope this maturity model empowers automation integrators and operators to make informed decisions when selecting fleet management systems and AMRs. The maturity model can also help direct vendor development efforts to ensure that their AMRs are able to support high-level HFMS, and differentiate themselves in an increasingly competitive space.
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