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Join us at the Warehouse Picking Automation Workshop at ICRA 2017 / Call for Abstract (2017/03/03)

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会員各位

このたび,本年5月にシンガポールで行われるIEEEのInternational Conference on Robotics and Automation(ICRA2017)において,下記のワークショップを企画し,採択されました.

是非ともご参加・ご投稿をご検討ください.

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CALL FOR ABSTRACT for
Warehouse Picking Automation Workshop 2017
(ICRA 2017 Full Day Workshop)

Webpage: http://wpaw17.kawso.com

The main aim of this workshop is to gather past and future participants of Amazon Robotics Challenge (formerly the Amazon Picking Challenge) and the robotics and automation community to discuss their robotic solutions, experience of the previous competitions and their vision on automating item picking for warehouse logistics. Attendees of the workshop will have the opportunity to see the state-of-the-art in item picking research and development and interact with the people who are passionate about solving this complex problem during the presentations, poster discussions, and open forums. This workshop is co-organized by Amazon Robotics, the sponsor of the Amazon Robotics Challenge.

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IMPORTANT DATES:
Abstract Submission: April 19, 2017 (23:59 PST)
Acceptance Notification: April 30, 2017
Workshop: 29 May 2017

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ABSTRACT:
– Abstract must be 2-4 pages long
– Follows IEEE Conference Format
– PDF version (6MB maximum file size)
– Submissions will be subject to review

=================================================================== SUBMISSION:
– Download template here:
(LATEX) http://ras.papercept.net/conferences/support/tex.php
(WORD) http://ras.papercept.net/conferences/support/word.php
– Send the abstract to: acauso@ntu.edu.sg
– With subject “[WPAW17 Submission]”

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TOPICS OF INTEREST INCLUDE BUT NOT LIMITED TO:
– Robotic Solutions ― The systems that could automatically pick items from inventory storage. The sub-systems (hardware design and software integration) that make up the whole solution and the integration process and lessons learned in building them.

– Grasp Strategy and Gripper Design ― The challenges of picking from a space-constrained shelf; The end-effector hardware designed, fabricated, and tested to address the problem; The processes, algorithms, and strategies to successfully pick target items.

– Perception ― The challenges of item identification and pose estimation in such a cluttered and constrained environment; The vision systems and other complementary sensors required to build a system to support the perception strategy; The perception strategy and algorithms leveraged or developed to correctly pick the target items; The advantages and disadvantages of some sensors & cameras over others.

– Strategy & Integration ― The rationale for the design of the competition; The identification of the sub-problems that define the grand problem of automated item picking in a warehouse; Strategies (hardware, software, or process) to overcome the engineering problems; The optimization strategies on planning and control to achieve a safe and efficient solution.

– Journey to Winning The Competition & Solving the Engineering Challenges ― The teams’ strategies to win the Amazon Robotics Challenge; The challenges of building a technical team and solving a complex problem within a short period of time; The trade-offs required and the milestones set to be able to build a competition-ready solution. The future outlook of the competition and the item-picking problem as an academic and industrial pursuit.

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AVAILABILITY OF WORKSHOP MATERIALS:
– Abstracts will be made available to the public prior to the workshop
– Videos of the workshop and other presented materials will be made available to the public after the workshop

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PUBLICATION OF EXTENDED ABSTRACTS:
– Extended version of the abstracts (6-8 pages), reviewed and edited, are planned to be compiled into a book on Warehouse Automation to be published by Springer. Please watch out for more details.

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SUPPORT:
This workshop is endorsed and supported by IEEE Robotics & Automation Society (IEEE-RAS) Technical Committee on Mobile Manipulation (TCMM)

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ORGANIZERS:
Albert Causo, Nanyang Technological University
Joey Durham, Amazon Robotics
Kris Hauser, Duke University
Kei Okada, University of Tokyo
Alberto Rodriguez, Massachusetts Institute of Technology

Looking forward to receiving your contributions!

配信元・問合先――――――――――――――――――――――――――――
岡田 慧
東京大学
k-okada@jsk.t.u-tokyo.ac.jp


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