Department of Computer Science


The key component of our project is the continuous integration of all developed algorithms and techniques into a real-world demonstrator to illustrate their practicability and usefulness. We have chosen warehousing and retail as our current application scenario: Robot-assisted inventory is applied in a supermarket as we expect goods to be labeled individually (with RFID tags) in the near future. This enables products to be tracked from production to sale consistently and to be localized continuously.

This scenario aims at synchronizing the product stock of supermarkets or stores automatically. Other sample tasks could be the identification of products that are past their sell-by dates or located in the wrong places.

In addition the robot localizes itself using the existing infrastructure of different, cost-efficient ambient wireless sensors. To achieve the location we develop and combine novel positioning techniques using passive UHF RFID, Bluetooth, and WLAN. We thereby employ three orthogonal measuring techniques: detection rates, signal strength, and round trip time. Due to their distinguishing read ranges, the technologies can complement each other at different scales of the environment. An effective and cost-efficient indoor location solution can only be achieved with multiple and heterogeneous ambient sensors combined together.

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