# Knowledge-Enabled Robotic Agents for Shelf Replenishment in Cluttered Retail Environments

arXiv: https://arxiv.org/abs/1605.04177 · HTML: https://mlsanity.com/paper/1605.04177/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 May 2016.

## Built on by (most cited first, 1 of 1)

- [Large Pre-Trained Models for Bimanual Manipulation in 3D](https://mlsanity.com/paper/2509.20579/) (2025)

## Abstract (arXiv)

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.