1 research outputs found
Knowledge-Enabled Robotic Agents for Shelf Replenishment in Cluttered Retail Environments
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.Comment: published in the proceedings of AAMAS 2016 as an extended abstrac