October 20, 2025

Pick-to-Tote: a technology that boosts warehouse efficiency

Companies are increasingly considering automation for order fulfillment.

This is not just a trend — it’s a necessity: growing order volumes, labor shortages, and pressure for speed are pushing businesses to explore new approaches.

One of the most promising scenarios is Pick to Tote — a method where the picker doesn’t go to the product; instead, the product “comes” to them on a robot.

But behind the apparent simplicity of the process lies one of the most technologically complex solutions in warehouse automation. Implementing Pick to Tote is far from easy, even for companies that develop WES systems.


How Pick to Tote Works

The core of the technology is that AMRs (Autonomous Mobile Robots) handle the transportation of totes, into which the operator places the items.
The process works like this:
  • The robot receives a task from the WES and calculates the optimal route to the picking station.
  • The picker works at a fixed station, while robots bring empty totes to them one by one.
  • After the order is picked, the robot takes the filled tote to the consolidation or shipping area.

This approach can reduce unnecessary warehouse travel by up to 70%, speed up order fulfillment, and decrease the physical strain on employees.

Why Pick to Tote Is Not Just a Workflow, but an Engineering System


For such a process to work, you need not just a WES, but a WES capable of managing the dynamic flow of robots and humans in real time.


Pick to Tote requires:
  • Precise synchronization across all system levels — from WMS to AMR controllers.
  • Multi-level route planning — robots must move without conflicts, delays, or congestion in narrow areas.
  • Predictive task allocation — the system must anticipate where and when a robot will be needed so the picker never waits.
  • Flexible task prioritization logic — balancing speed, safety, and workforce utilization.
  • Deep integration with equipment — robots, scanners, conveyors, scales — and adaptation to the specifics of each warehouse.

This is not an off-the-shelf solution. You cannot simply “connect a robot to the system.” Every integration requires configuring routing algorithms, safety zones, and data exchange interfaces.



Why Not All WES Companies Can Do This


Many warehouse management systems handle the orchestration of people and conveyors quite well.
But when mobile robots are introduced, especially in Pick to Tote scenarios, a whole set of engineering challenges arises that standard WES cannot handle.

Key Reasons:
  • WES architecture is not designed for dynamic objects. The system must respond instantly to changes in the environment: if one robot is delayed, another must be able to reroute immediately.
  • Lack of an internal planning and flow simulation module. Without this, it is impossible to predict how dozens of robots will behave under real operational load.
  • Insufficient integration with robotic platforms. Proper operation requires native connectors and APIs, rather than third-party add-ons.
  • Limited expertise in engineering modeling. Pick-to-Tote is not just about IT; it requires a deep understanding of warehouse physics, including flow logistics, safety, and workplace ergonomics.

Outcome: Many companies can offer “simplified” scenarios with partial automation, but few are capable of implementing a true Pick-to-Tote system, where humans and robots operate seamlessly as a unified system.


How Displine Solves This Challenge


The Displine team is building a next-generation WES designed for seamless interaction with AMRs, conveyors, and humans within a unified system.


Our engineering solutions include:
  • Intelligent routing algorithms – the system dynamically assigns tasks to robots in real time, preventing collisions and downtime.
  • Assembly station load planner – ensures that human operators are consistently supported by robots without creating queues.
  • Accurate integration with WMS and equipment – a single database with continuous event exchange for smooth operation.
  • Modeling and simulation tools – enable testing of scenarios before deployment in a live warehouse environment.
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