Mobile robots: fleet planning by rules, charging by threshold
Fleets of mobile robots lose throughput to rule-based planning and threshold charging. How optimised planning and low-level control can be checked.
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Fleet planning for mobile robots runs on rules
What happens. Tasks are given to the nearest free robot, and routes are decided by simple priority rules. With more robots, the aisles jam, robots wait for each other, and some tasks sit long in the queue.
What it costs. Throughput: the fleet delivers less than the number of robots suggests, and customers add robots to make up for it.
Why the usual fix fails. More rules for each special case make the planner hard to maintain, and a rule that helps in one layout hurts in another. Adding robots raises cost and traffic.
How a fixed-price remote diagnosis checks it. From fleet logs (task times, waiting, routes, queues) and the layout I check how an optimised assignment and traffic plan would have run. The fixed-price remote diagnosis shows how much throughput planning could add before robots are bought.
Background: Optimal paths and setpoint plans
Robot batteries are charged by threshold
What happens. A robot drives to the charger when its battery falls below a set level. When several robots reach the threshold together, they queue at the chargers while the tasks wait.
What it costs. Fleet availability: robots out of work at the busiest times, and chargers that stand idle at others. Batteries wear faster from deep discharge and fast charging.
Why the usual fix fails. A higher threshold keeps robots safer but charges them more often. More chargers cost space and money.
How a fixed-price remote diagnosis checks it. From charge logs, task plans and battery data I check how a charging plan that looks ahead at the tasks would have used the chargers. The fixed-price remote diagnosis tells you how much availability planned charging could add and what the robot software must provide.
Background: Economic predictive control
Low-level control and actuators for warehouse robots
What happens. Warehouse robots need drive control that is smooth, accurate and efficient: wheels, lifting axes, grippers. The people who can design it from the motor up are few, and they are needed by every robot maker.
What it costs. Development waits for control engineers. Robots with poor low-level control are jerky, wear faster and use more energy.
Why the usual fix fails. Off-the-shelf drive settings are tuned for a general case. A new hire takes months to become useful, and an in-house team for a single product is hard to justify.
How a fixed-price remote diagnosis checks it. From motor and drive data of a prototype I identify the actuators and check how model-based control would improve smoothness and efficiency. The fixed-price remote diagnosis gives your team an outside view of the drive control before it is frozen for production.
Background: Predictive drive control
More problems that concern this industry
These problems are described on the page of the industry where they matter most:
- Mobile robots lose their position in the warehouse (Logistics and warehouse operators)
- Robots keep conservative speeds near people and obstacles (Robot maker)
Check it on your plant first: a fixed-price remote diagnosis
EUR 4,500 net · 5 working days · remote · availability on request · freelance or through temporary agency work
Within a fixed scope and at a fixed price, I review your data, control structure and measurements remotely and tell you whether the problem on this page is behind your symptoms and what fixing it would take. You get a short summary for decision-makers and a technical report for your engineers.