Delivery robots on foot and bike paths: new research project creates required data base

Autonomous delivery robot in action.
How can parcels be delivered at unusual times of the day? Which location is worthwhile for a new robot based pizza service? The vision of autonomous delivery robots and autonomous micromobiles in urban areas poses new challenges for infrastructure.

Where can such a system even move safely? What number of pedestrians is suitable for robot use? The currently available data does not yet provide a complete answer to these questions. A new joint project therefore combines the competencies of various universities and colleges as well as industrial partners in order to identify methods for efficient data collection based on bicycle movements. The Federal Ministry for Digital Affairs and Transport (BMDV) is funding the project with 2,9 million euros.

"While very detailed map data is already available for the autonomous motor vehicle today, it doe not exist for the much more varied foot and bike paths," says project manager Prof. Sebastian Zug, head of the Professorship for Software Technology and Robotics at the TU Bergakademie Freiberg. "So if we want to know where a pizza service should open in a given district in order to reach many customers, we cannot answer the question by looking at available routes, their widths and the volume of traffic.“ The research project “Ready for Smart City Robots? Multimodal maps for autonomous micromobiles - R4R" is examining which strategies can collect and evaluate such data as part of the mFUND innovation initiative of the BMDV.

Detailed maps of walking and cycling paths necessary

The manual collection of all necessary data is not feasible due to the total length of footpaths and cycle paths. That is why the team relies on the involvement of cyclists in order to capture the surfaces of pavements and the position of bollards or heels over a large area, as well as pedestrian traffic, lighting situation or localization accuracy. "If such data exists, then only in part at very different places in municipalities or public databases. A holistic evaluation is not possible in this way, "says the project manager. The R4R project pursues two strategies: firstly, data collection with rental bicycles and a compact sensor node and, secondly, the use of a smartphone app by voluntary bicycle enthusiasts. The team now wants to find out which method is most efficient for data collection in the next three years. In addition, the researchers are interested in how the data can be presented in such a way that they answer as many research questions as possible regarding autonomous small robots.

Data collection with special sensors on bicycles

In a previous project, the researchers developed a sensor set and an app for bicycles. With the help of volunteers in Magdeburg, Braunschweig, Freiberg and other municipalities, they already covered around 16.600 kilometres. The data sets obtained from the voluntary cyclists now form the basis for the further development of the collection and processing chain and are compared in a first project phase with the reference data collected in the field by a robot. Based on this, the two survey methods are tested in non-urban areas – the evaluation is carried out in the city of Köthen and the district of North Saxony.

"The new project thus contributes to the data-driven development of intelligent mobility and logistics concepts that cover the specific characteristics and needs of different settlement areas and the people living there," says Prof. Sebastian Zug. R4R thus also contributes to the structural change in the Central German territory. The project officially starts with a kick-off event on 26th September in Köthen.

The universities of Freiberg and Magdeburg as well as the universities of Anhalt, Köthen and Merseburg are involved in the joint project. The companies Endiio Engineering GmbH, TINK GmbH, DigiPL GmbH, CyFace GmbH, PTV GmbH as well as the district of North Saxony support the joint project.

Background: About the mFUND of the BMDV

As part of the mFUND innovation initiative, the BMDV has been funding data-based research and development projects for the digital and networked mobility of the future since 2016 The project funding is complemented by an active professional networking between actors from politics, business, administration and research and by the provision of open data on the Mobilithek. Further information can be found at www.mFUND.de.

Logo BMDV

Logo mFund

Fragen beantwortet / Contact: 
Prof. Sebastian Zug, sebastian.zug@informatik.tu-freiberg.de