Advances on Robotic Item Picking: Applications in Warehousing and E-Commerce Fulfillment

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

Research output: Book/Report/Conference proceedingBook

Abstract

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.

Original languageEnglish (US)
PublisherSpringer
Number of pages152
ISBN (Electronic)9783030356798
ISBN (Print)9783030356781
DOIs
StatePublished - Jan 1 2020
Externally publishedYes

Keywords

  • Amazon robotics challenge
  • Automated item picking
  • Gripper design
  • Machine learning for object identification
  • Robotic grasping
  • Warehouse automation

ASJC Scopus subject areas

  • General Engineering
  • General Computer Science

Fingerprint

Dive into the research topics of 'Advances on Robotic Item Picking: Applications in Warehousing and E-Commerce Fulfillment'. Together they form a unique fingerprint.

Cite this