AutoKoWaT

Motivation

Today, goods handling systems are overwhelmed in dynamic environments with open, unorganized workspaces and changing tasks. Neither the existing sensors nor the operating software are suitable for autonomous operations under these conditions. Ensuring high operational reliability is only possible here at the expense of efficiency and limits usability.

Goals and procedure

In the AutoKoWaT project, self-driving transport systems are to be enabled by additional photonic components, first and foremost sensors and artificial intelligence, to solve a wide range of logistics tasks in complex, dynamic situations, either alone or in a swarm. The innovative sensor technology is to capture the workspace in a 3D multimodal imaging, predictive and dynamically robust manner. From the data, relevant workspace objects are identified, located, semantically analyzed, and appropriate actions are derived. To ensure lowest system latencies, the optimized design of photonic components as well as their interaction with mechanisms of mutual control are development goals. Components for a guidance and control system are developed for the interaction of photonics and robotics.

Innovation and perspectives

The approach of photonic add-ons consisting of novel 3D-sensory components and solutions for intelligent on-site processing and process control pursued in AutoKoWaT allows the use under challenging conditions of dynamic goods transport use cases as well as in a variety of other applications. The results of the project are to form the basis for the development of marketable product solutions that can be used in many industries.

This project is funded by the Federal Ministry of Education and Research of Germany (BMBF) (grant no.~13N16336)