# Off-the-shelf bin picking workcell with visual pose estimation: A case study on the world robot summit 2018 kitting task

arXiv: https://arxiv.org/abs/2309.16221 · HTML: https://mlsanity.com/paper/2309.16221/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 36 references that are in the map.
- First posted on arXiv 28 Sep 2023.

## Builds on (most cited first, 5 of 5)

- [BOP Challenge 2020 on 6D Object Localization](https://mlsanity.com/paper/2009.07378/) (2020)
- [BlenderProc](https://mlsanity.com/paper/1911.01911/) (2019)
- [Robots Assembling Machines: Learning from the World Robot Summit 2018 Assembly Challenge](https://mlsanity.com/paper/1911.05884/) (2019)
- [ParaPose: Parameter and Domain Randomization Optimization for Pose Estimation using Synthetic Data](https://mlsanity.com/paper/2203.00945/) (2022)
- [Autonomous Industrial Assembly using Force, Torque, and RGB-D sensing](https://mlsanity.com/paper/2002.02580/) (2020)

## Built on by (most cited first, 3 of 3)

- [Good Grasps Only: A data engine for self-supervised fine-tuning of pose estimation using grasp poses for verification](https://mlsanity.com/paper/2409.11512/) (2024)
- [Object Pose Distribution Estimation for Determining Revolution and Reflection Uncertainty in Point Clouds](https://mlsanity.com/paper/2512.07211/) (2025)
- [Towards a Modular Bin-picking Framework for Handling Object Pose Uncertainties](https://mlsanity.com/paper/2607.13698/) (2026)

## Abstract (arXiv)

The World Robot Summit 2018 Assembly Challenge included four different tasks. The kitting task, which required bin-picking, was the task in which the fewest points were obtained. However, bin-picking is a vital skill that can significantly increase the flexibility of robotic set-ups, and is, therefore, an important research field. In recent years advancements have been made in sensor technology and pose estimation algorithms. These advancements allow for better performance when performing visual pose estimation. This paper shows that by utilizing new vision sensors and pose estimation algorithms pose estimation in bins can be performed successfully. We also implement a workcell for bin picking along with a force based grasping approach to perform the complete bin picking. Our set-up is tested on the World Robot Summit 2018 Assembly Challenge and successfully obtains a higher score compared with all teams at the competition. This demonstrate that current technology can perform bin-picking at a much higher level compared with previous results.