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相关论文: Design and Development of an automated Robotic Pic…

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Robots that autonomously manipulate objects within warehouses have the potential to shorten the package delivery time and improve the efficiency of the e-commerce industry. In this paper, we present a robotic system that is capable of both…

Robotic picking from cluttered bins is a demanding task, for which Amazon Robotics holds challenges. The 2017 Amazon Robotics Challenge (ARC) required stowing items into a storage system, picking specific items, and packing them into boxes.…

In response to the growing challenges of manual labor and efficiency in warehouse operations, Amazon has embarked on a significant transformation by incorporating robotics to assist with various tasks. While a substantial number of robots…

机器人学 · 计算机科学 2025-07-30 Owais Ahmed , M Huzaifa , M Areeb , Hamza Ali Khan

This paper presents a robotic pick-and-place system that is capable of grasping and recognizing both known and novel objects in cluttered environments. The key new feature of the system is that it handles a wide range of object categories…

This paper describes Team Delft's robot, which won the Amazon Picking Challenge 2016, including both the Picking and the Stowing competitions. The goal of the challenge is to automate pick and place operations in unstructured environments,…

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…

计算机视觉与模式识别 · 计算机科学 2017-07-25 Wim Abbeloos , Fabian Gouwens , Simon Jansen , Berend Küpers , Maurice Ramaker , Toon Goedemé

We present a research picking prototype related to our company's industrial waste sorting application. The goal of the prototype is to be as autonomous as possible and it both calibrates itself and improves its picking with minimal human…

机器人学 · 计算机科学 2015-11-25 Janne V. Kujala , Tuomas J. Lukka , Harri Holopainen

This paper presents a overview of the inaugural Amazon Picking Challenge along with a summary of a survey conducted among the 26 participating teams. The challenge goal was to design an autonomous robot to pick items from a warehouse shelf.…

This paper presents a vision based robotic system to handle the picking problem involved in automatic express package dispatching. By utilizing two RealSense RGB-D cameras and one UR10 industrial robot, package dispatching task which is…

机器人学 · 计算机科学 2019-04-10 Shengfan Wang , Xin Jiang , Jie Zhao , Xiaoman Wang , Weiguo Zhou , Yunhui Liu

We present placing via picking (PvP), a method to autonomously collect real-world demonstrations for a family of placing tasks in which objects must be manipulated to specific, contact-constrained locations. With PvP, we approach the…

机器人学 · 计算机科学 2024-12-30 Oliver Limoyo , Abhisek Konar , Trevor Ablett , Jonathan Kelly , Francois R. Hogan , Gregory Dudek

Efficient and safe retrieval of stacked objects in warehouse environments is a significant challenge due to complex spatial dependencies and structural inter-dependencies. Traditional vision-based methods excel at object localization but…

机器人学 · 计算机科学 2025-03-31 Abhinav Pathak , Rajkumar Muthusamy

In recent years, the throughput requirements of e-commerce fulfillment warehouses have seen a steep increase. This has resulted in various automation solutions being developed for item picking and movement. In this paper, we address the…

机器人学 · 计算机科学 2021-09-28 Avnish Gupta , Akash Jadhav , Pradyot VN Korupolu

We consider the problem of sorting a densely cluttered pile of unknown objects using a robot. This yet unsolved problem is relevant in the robotic waste sorting business. By extending previous active learning approaches to grasping, we show…

机器人学 · 计算机科学 2016-09-06 Janne V. Kujala , Tuomas J. Lukka , Harri Holopainen

This work demonstrates how autonomously learning aspects of robotic operation from sparsely-labeled, real-world data of deployed, engineered solutions at industrial scale can provide with solutions that achieve improved performance.…

Autonomous robotic manipulation in clutter is challenging. A large variety of objects must be perceived in complex scenes, where they are partially occluded and embedded among many distractors, often in restricted spaces. To tackle these…

计算机视觉与模式识别 · 计算机科学 2018-10-03 Max Schwarz , Anton Milan , Arul Selvam Periyasamy , Sven Behnke

Automating warehouse operations can reduce logistics overhead costs, ultimately driving down the final price for consumers, increasing the speed of delivery, and enhancing the resiliency to workforce fluctuations. The past few years have…

机器人学 · 计算机科学 2023-06-28 Shuai Li , Azarakhsh Keipour , Kevin Jamieson , Nicolas Hudson , Charles Swan , Kostas Bekris

The choice of a grasp plays a critical role in the success of downstream manipulation tasks. Consider a task of placing an object in a cluttered scene; the majority of possible grasps may not be suitable for the desired placement. In this…

机器人学 · 计算机科学 2023-04-11 Zhanpeng He , Nikhil Chavan-Dafle , Jinwook Huh , Shuran Song , Volkan Isler

Segmentation and tracking of unseen object instances in discrete frames pose a significant challenge in dynamic industrial robotic contexts, such as distribution warehouses. Here, robots must handle object rearrangement, including shifting,…

机器人学 · 计算机科学 2023-11-07 Yi Li , Muru Zhang , Markus Grotz , Kaichun Mo , Dieter Fox

We present a robotic system for picking a target from a pile of objects that is capable of finding and grasping the target object by removing obstacles in the appropriate order. The fundamental idea is to segment instances with both visible…

机器人学 · 计算机科学 2020-01-22 Kentaro Wada , Shingo Kitagawa , Kei Okada , Masayuki Inaba

A Robotic Mobile Fulfillment System is a robotised parts-to-picker system that is particularly well-suited for e-commerce warehousing. One distinguishing feature of this type of warehouse is its high storage modularity. Numerous robots are…

机器人学 · 计算机科学 2021-06-07 Adrien Rimélé , Philippe Grangier , Michel Gamache , Michel Gendreau , Louis-Martin Rousseau
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