# A Summary of Team MIT's Approach to the Amazon Picking Challenge 2015

arXiv: https://arxiv.org/abs/1604.03639 · HTML: https://mlsanity.com/paper/1604.03639/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Apr 2016.

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

- [Sample-Efficient Safety Assurances using Conformal Prediction](https://mlsanity.com/paper/2109.14082/) (2021)
- [Mechanical Search on Shelves using a Novel "Bluction" Tool](https://mlsanity.com/paper/2201.08968/) (2022)
- [OptiGrasp: Optimized Grasp Pose Detection Using RGB Images for Warehouse Picking Robots](https://mlsanity.com/paper/2409.19494/) (2024)

## Abstract (arXiv)

The Amazon Picking Challenge (APC), held alongside the International Conference on Robotics and Automation in May 2015 in Seattle, challenged roboticists from academia and industry to demonstrate fully automated solutions to the problem of picking objects from shelves in a warehouse fulfillment scenario. Packing density, object variability, speed, and reliability are the main complexities of the task. The picking challenge serves both as a motivation and an instrument to focus research efforts on a specific manipulation problem. In this document, we describe Team MIT's approach to the competition, including design considerations, contributions, and performance, and we compile the lessons learned. We also describe what we think are the main remaining challenges.