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Titlebook: Advances on Robotic Item Picking; Applications in Ware Albert Causo,Joseph Durham,Alberto Rodriguez Book 2020 Springer Nature Switzerland A

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發(fā)表于 2025-3-21 18:14:46 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Advances on Robotic Item Picking
期刊簡(jiǎn)稱(chēng)Applications in Ware
影響因子2023Albert Causo,Joseph Durham,Alberto Rodriguez
視頻videohttp://file.papertrans.cn/151/150323/150323.mp4
發(fā)行地址Presents an inside look at the various solutions for automated warehouse item picking based on the Amazon Robotics Challenge (ARC).Contains details of the challenges and solutions involved in automati
圖書(shū)封面Titlebook: Advances on Robotic Item Picking; Applications in Ware Albert Causo,Joseph Durham,Alberto Rodriguez Book 2020 Springer Nature Switzerland A
影響因子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 co
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Team UAlberta: Amazon Picking Challenge Lessons,hing and grasping objects deep inside the shelve bins. Given limited resources we come up with a simple design, a custom-made mechanism to bring objects to the edge of the shelve bins. During trials we explored both image-based visual servoing and Kinect RGB-D vision. The former, while precise, reli
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A Soft Robotics Approach to Autonomous Warehouse Picking,d be able to pick objects with various shape, size, and physical properties. It was shown that soft robots, thanks to the elasticity included in their structure in design, are adaptable to grasp different objects and robust to interact in unstructured environments. In this paper, we present a soft r
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,Standing on Giant’s Shoulders: Newcomer’s Experience from the Amazon Robotics Challenge 2017,teams to push the state of the art. In this chapter, we present the approach, design philosophy and development strategy that we followed during our participation in the Amazon Robotics Challenge 2017, a competition focused on warehouse automation. After introducing our solution, we detail the devel
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