Team Applied Robotics: A closer look at our robotic picking system

TL;DR

This paper presents Team Applied Robotics' comprehensive robotic picking system designed for the Amazon Picking Challenge 2016, integrating advanced vision, detection, and manipulation strategies for diverse product handling.

Contribution

It introduces a complete robotic picking system with novel integration of high-resolution 3D vision, combined detection algorithms, and optimized path planning for complex object retrieval.

Findings

Successful handling of diverse products in competition scenarios

Effective integration of vision and manipulation components

Improved accuracy in object detection and picking efficiency

Abstract

This paper describes the vision based robotic picking system that was developed by our team, Team Applied Robotics, for the Amazon Picking Challenge 2016. This competition challenged teams to develop a robotic system that is able to pick a large variety of products from a shelve or a tote. We discuss the design considerations and our strategy, the high resolution 3D vision system, the use of a combination of texture and shape-based object detection algorithms, the robot path planning and object manipulators that were developed.