Team Applied Robotics: A closer look at our robotic picking system
This addresses the challenge of automating warehouse picking tasks for logistics and robotics applications, but it is incremental as it builds on existing competition frameworks.
The paper describes a vision-based robotic picking system developed for the Amazon Picking Challenge 2016, which tackled the problem of picking diverse products from shelves or totes, resulting in a system that integrates high-resolution 3D vision, object detection algorithms, and robot path planning.
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.