Deep learning for vision guided robotics

Automating logistics

The team

Herbert ten HaveCEO

Kanter van DeurzenCTO

The team

Laurens van WijkCOO

Prof.Dr.Ir. Martijn WisseAdvisor

Logistics contains many heavy and repetitive tasks

Majority of warehouses (>80%) are manually operated

Labor is physically heavy and repetitive

Allowed margin of error is low

Main costs of operation:Warehousing: Order picking (>55%)

Postal sorting: Singulation (>65%)

Within the logistic sector variation is standard:

- Products vary- Packaging varies- Stacks vary

In order to automate these environments an effective and scalable solution for variation is needed.

Conventional robotics fail to handle product variation

Market opportunity

The global logistics robots market was valued at $3,060 million in 2015

Projection for 2021 is $10,518 millionCAGR of 25.4% from 2017 to 2021

Picking robots contributed to the highest share of this market

E-commerce is one of the biggest drivers. This will affect mainly warehousing and

postal services

Artificial intelligence

Picking

Through deep learning robots can learn to handle variation

Depalletizing

Quality control

We excel in determining Grasp Locations for Varying Objects through Deep Learning

Applications & markets

What?

Order pickingBin picking

Quality controlIdentification

For whom?

WarehousingPostal sector

Logistcs track record (a selection)

Warehousing logistics Parcel handling

End users

Integrators

Conversing with

www.fizyr.comh.tenhave@fizyr.com+31 6 53555955