Advances on Robotic Item Picking

Applications in Warehousing & E-Commerce Fulfillment

Albert Causo, Joseph Durham, Kris Hauser, Kei Okada, Alberto Rodriguez

• Publisher: Springer
• Year: 2020
• Print ISBN:
  9783030356781
• eBook ISBN:
  9783030356798
• Topic: Technology & Engineering
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Technology & Engineering

This book is a compilation of advanced research and applications on robotic item picking and warehouse automation for e-commerce applications. The works in this book are based on results that came out of the Amazon Robotics Challenge from 2015-2017, which focused on fully automated item picking in a warehouse setting, a topic that has been assumed too complicated to solve or has been reduced to a more tractable form of bin picking or single-item table top picking. The book's contributions reveal some of the top solutions presented from the 50 participant teams. Each solution works to address the time-constraint, accuracy, complexity, and other difficulties that come with warehouse item picking. The book covers topics such as grasping and gripper design, vision and other forms of sensing, actuation and robot design, motion planning, optimization, machine learning and artificial intelligence, software engineering, and system integration, among others. Through this book, the authors describe how robot systems are built from the ground up to do a specific task, in this case, item picking in a warehouse setting. The compiled works come from the best robotics research institutions and companies globally.

Table of contents

• Cover
• Front Matter
• Team CVAP’s Mobile Picking System at the Amazon Picking Challenge 2015
• Team UAlberta: Amazon Picking Challenge Lessons
• A Soft Robotics Approach to Autonomous Warehouse Picking
• Top-Down Approach to Object Identification in a Cluttered Environment Using Single RGB-D Image and Combinational Classifier for Team Nanyang’s Robotic Picker at the Amazon Picking Challenge 2015
• Team KTH’s Picking Solution for the Amazon Picking Challenge 2016
• End-to-End Learning of Object Grasp Poses in the Amazon Robotics Challenge
• A Systems Engineering Analysis of Robot Motion for Team Delft’s APC Winner 2016
• Standing on Giant’s Shoulders: Newcomer’s Experience from the Amazon Robotics Challenge 2017
• Team C2M: Two Cooperative Robots for Picking and Stowing in Amazon Picking Challenge 2016
• Description of IITK-TCS System for ARC 2017
• Designing Cartman: A Cartesian Manipulator for the Amazon Robotics Challenge 2017
• Back Matter