Delivery robots are not just small autonomous cars! How to close the gap in environmental data for planning their operation?

The configuration of autonomous cars (maximum dimension, features, behavior rules) and the operation area are well-defined. Hence, for a dedicated road, the mission planner can assume that the system can move on it, at least in principle. For smaller robots operating on footpaths and cycle tracks this prior knowledge does not exist. From an infrastructure perspective, for example, the widths of pedestrian and bicycle vary widely and integrate different types of obstacles. On the other hand, the robot itself (size, kinematics, sensory equipment, etc.) is not standardized. For mapping infrastructure and robot’s properties, a time-consuming manual analysis and experiments with the actual robot in the intended area of operation is necessary. This approach is unrealistic for the real-world, wide spread application of mobile robots - the data for the navigability analysis must be collected using a different strategy.In order to automate this process, the paper examines the state of the art in the collection of environmental data. It extracts the parameters relevant for the operation of a robotic system from previous work, compares them with established data collections/services and identifies their limits when analyzing possible application areas. Building on this, the paper evaluates 150 projects that aim to close these gaps with different concepts. The article structures and classifies the projects and analyses their focal points. We can conclude that only a multi-model approach is able to address the complexity of acquiring all necessary environmental data with a high coverage. Additionally, with that analysis, we provide methodological support to plan future robotic applications.