ARMBench: An object-centric benchmark dataset for robotic manipulation
This paper introduces Amazon Robotic Manipulation Benchmark (ARMBench), a large-
scale, object-centric benchmark dataset for robotic manipulation in the context of a …
scale, object-centric benchmark dataset for robotic manipulation in the context of a …
End-to-end learning of object grasp poses in the Amazon Robotics Challenge
Abstract The Amazon Robotics Challenge (ARC) is a robotics competition aimed to advance
warehouse automation. One of the engineering challenges is making the system robust to …
warehouse automation. One of the engineering challenges is making the system robust to …
Nimbro picking: Versatile part handling for warehouse automation
Part handling in warehouse automation is challenging if a large variety of items must be
accommodated and items are stored in unordered piles. To foster research in this domain …
accommodated and items are stored in unordered piles. To foster research in this domain …
Fast object learning and dual-arm coordination for cluttered stowing, picking, and packing
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 …
challenges. The 2017 Amazon Robotics Challenge (ARC) required stowing items into a …
MetaGraspNetV2: All-in-one dataset enabling fast and reliable robotic bin picking via object relationship reasoning and dexterous grasping
Grasping unknown objects in unstructured environments is one of the most challenging and
demanding tasks for robotic bin picking systems. Developing a holistic approach is crucial to …
demanding tasks for robotic bin picking systems. Developing a holistic approach is crucial to …
Standing on giant's shoulders: Newcomer's experience from the Amazon Robotics Challenge 2017
GA Garcia Ricardez, L El Hafi… - Advances on robotic item …, 2020 - Springer
International competitions have fostered innovation in fields such as artificial intelligence,
robotic manipulation, and computer vision, and incited teams to push the state of the art. In …
robotic manipulation, and computer vision, and incited teams to push the state of the art. In …
Integrating different levels of automation: Lessons from winning the amazon robotics challenge 2016
CH Corbato, M Bharatheesha… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
This paper describes Team Delft's robot winning the Amazon Robotics Challenge 2016. The
competition involves automating pick and place operations in semistructured environments …
competition involves automating pick and place operations in semistructured environments …
Cartman: The low-cost cartesian manipulator that won the amazon robotics challenge
D Morrison, AW Tow, M Mctaggart… - … on robotics and …, 2018 - ieeexplore.ieee.org
The Amazon Robotics Challenge enlisted sixteen teams to each design a pick-and-place
robot for autonomous warehousing, addressing development in robotic vision and …
robot for autonomous warehousing, addressing development in robotic vision and …
Deep learning-based object classification and position estimation pipeline for potential use in robotized pick-and-place operations
Accurate object classification and position estimation is a crucial part of executing
autonomous pick-and-place operations by a robot and can be realized using RGB-D …
autonomous pick-and-place operations by a robot and can be realized using RGB-D …
Learning affordance segmentation for real-world robotic manipulation via synthetic images
This letter presents a deep learning framework to predict the affordances of object parts for
robotic manipulation. The framework segments affordance maps by jointly detecting and …
robotic manipulation. The framework segments affordance maps by jointly detecting and …