  Autonomous robots in unstructured and dynamically changing retail
environments have to master complex perception, knowledgeprocessing, and
manipulation tasks. To enable them to act competently, we propose a framework
based on three core components: (o) a knowledge-enabled perception system,
capable of combining diverse information sources to cope with occlusions and
stacked objects with a variety of textures and shapes, (o) knowledge processing
methods produce strategies for tidying up supermarket racks, and (o) the
necessary manipulation skills in confined spaces to arrange objects in
semi-accessible rack shelves. We demonstrate our framework in an simulated
environment as well as on a real shopping rack using a PR2 robot. Typical
supermarket products are detected and rearranged in the retail rack, tidying up
what was found to be misplaced items.
