Maru and Toru:
Item-specific logistics solutions based on ROS

Moritz Tenorth, Ulrich Klank and Nikolas Engelhard{ tenorth, klank, engelhard } @ magazino.eu

Magazino GmbH
Landsberger Str. 23480687 München
T +49-89-21552415-0
F +49-89-21552415-9
info@magazino.eu
www.magazino.eu

In today’s warehouses

it’s always either man-to-goods or goods-to-man,
but the human is still the central factor in all intralogistics processes.
Man to goods

Dependence on staff
High salary and process costs

Goods to man

Missing flexibility
Missing scalability
High initial investment
No individual object grasping3

Our vision

is to scale from less complex objects and stationary operation towards mobility and applications
beyond logistics.

multi-robot
mobileAdditional applications

single-robot
stationary
less complex objects

complex objects
4Introducing TORU,an „automated contract worker“, a robot as flexible as the humanthat collaborates with the human and picks items directly from the shelf.

Item-specific handling in logistics requires new robotics concepts
to deal with the increased uncertainty and the diversity of objects to be picked.

Current warehouse automation

Perception-controlled logistics robots- Highly structured, static environment with minimized
uncertainty- Reliability achieved by carefully engineered components- Either 100% or no automation- Robots navigating freely between shelves designed for humans,
picking a wide range of objects- Dynamic environments with high uncertainty, flexible adaptation
to novel objects, tasks and warehouses- Scalability and reliability through redundant teams of robots- Human-machine collaboration allowing incremental automation

 Highly deterministic environment

 Highly autonomously acting robots- Rack feeder on rails, standardized carriers, recurring tasks

7New programming approaches enabled by ROS

are needed because classical PLC programming does not scale well to perception- andcloud-based robotics tasks.

Current warehouse automation

Perception-controlled logistics robots- Environment is completely known at programming time, somovements can be predefined- Low uncertainty requires only few sensors at well-known
positions- Programs remain the same over the lifetime of a system- Environment is dynamic, so robots have to plan motions atruntime after perceiving objects and react to events and errors- Seamless integration of object perception for dealing withuncertainty- Fast adaptation of control programs through task editor, databaseconnections and cloud infrastructure Offline programming of mostly sequential tasks

 Reactive and perception-guided control programs
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Where are we?

9What have we learned?

And how does ROS help us achieve our goals?

1. Perception has to be an integral part of the system, not a one-time task
2. Databases and persistent information storage are crucial components
3. Only few parts of the system have to be real-time
4. Developing software in simulation parallel to the hardware allows fast iterations
5. The ROS community, common practices and (still) ease of use are important10Perception needs to be an integral part of the control systemfor object recognition and run-time adaptation and correction of robot movements.

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Databases and persistent information storage are crucial

for managing environment information and for making sure that important data on theexecution state is not lost.

Persistent storage ofEnvironment stateRobot state (e.g. object picked?)
Error states
Parameters
Log data and statisticalinformation

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Not all parts of the control system have to be real-time,

which allows for much faster and more convenient development of higher-level algorithms.

Real time controllers directly on
the plug-and-drive motors

CANopen interface to ROS

All medium- and high-level
control in ROS in a non-realtime
environmentFacilitated and sped-up
development
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Developing SW and HW in parallelusing simulation and hardware abstraction allows to speed up iterative development ofnew robot systems.

Agile SW/HW development:





Rough design in CAD program
Export to simulation model
Production using 3D printers
Test the first prototype only few
days after the idea came up
Identify shortcomings, improve
design, continue with next
iteration

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ROS is the environment we feel comfortable in(as well as many recent robotics graduates)Common workflow for installing,building, launching, debugging
packagesMulti-language build system

Flexible development on different
computers, languages, OS,architectures

(Still) easy to useHelps with hiring and onboarding
new employees that know ROS
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Some of our use cases are not yet covered by ROS
and therefore require custom solutions for now

Varying quality of software components

ROS Industrial: ratings and metrics for assessing code quality
Currently, we mostly use well-tested core components and our own packages

High-level task coordination libraries

Integration of the runtime communication with persistent information storageSupport for (remote) debugging, logging, performance analysis, statistics

Multi- and many-robot systems: task allocation, navigation planning etc.
How much do the robots need to know about each other? How much communication is actually needed?

16Conclusions

New applications such as item-specific logistics require newprogramming approaches not provided by classical automation tools

ROS is well suited to these problems and supports rapid development ofrobot products

The community, common approaches and standard workflows arehelpful for hiring and onboarding developers in a startup company



We hope the ease of use and vibrant community will remain intact
Incremental evolution and migration paths would help us to adapt tofuture versions of ROS and stay connected to the community

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Welcome in our office
MAGAZINO GmbH
Landsberger Str. 234
80687 München
Germany

info@magazino.eu
www.magazino.eu

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