Project name: Automatic Map Calibration for Autonomous Warehousing
Project acronym: AMaCal
Dates: July 2016 – November 2017
Funding: HAMAG-BICRO (PoC6)

The goal of the  project is proof of concept evaluation and market potential analysis of an innovative method for improving autonomous forklift navigation in warehouses.

Automated pallet stacking

If proven feasible, the proposed method would significantly reduce the commissioning costs and increase the flexibility of operations in warehouses equipped with autonomous forklifts. This would remove a big barrier on the way towards wider adoption of fully autonomous vehicles in logistic operations.

The proposed solution uses raw distance measurements from laser scanners to build a map of the environment. The generated map is calibrated against a CAD floor plan of the warehouse in a straightforward interactive procedure. CAD floor plans are readily available, as they are commonly used for planning warehousing operations. If proven feasible, this  calibration procedure would enable  autonomous warehouse commissioning, which would result in significant savings.

The main objectives of the project are the implementation of the  calibration procedure and its validation. In addition to validating the technical feasibility of the proposed solution, it is our objective to evaluate its market potential and perform preliminary steps towards IP protection.

The implementation of the project is planned in three phases. In the first phase, we will implement the prototype, and its functionality will be evaluated in laboratory conditions. In the second phase, the functionality will be evaluated in industrial conditions, with the support of partner companies. The third phase will be dedicated to market analysis, preliminary IP protection and the development of a commercialization strategy.

Project results:

• Developed software prototype and submitted international patent application for interactive SLAM map calibration procedure
• Verification of closed loop control using only natural environment features for localization on an AGV in an industrial environment
• Numerous contributions to Google Cartographer open source SLAM

Collaboration with industrial partners: System Logistics,  Konzum,  Phoenix LiDAR Systems.