Abstract
Automated grasping has a long history of research that is increasing due to interest from industry. One grand challenge for robotics is Universal Picking: the ability to robustly grasp a broad variety of objects in diverse environments for applications from warehouses to assembly lines to homes. Although many researchers now openly share code and data, it is challenging to compare and/or reproduce experimental results to identify which aspects of which approaches work best due to variations in assumptions and experimental protocols, e.g., sensors, lighting, robot arms, grippers, and objects.
Original language | English |
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Pages (from-to) | 1440-1442 |
Number of pages | 3 |
Journal | IEEE Transactions on Automation Science and Engineering |
Volume | 15 |
Issue number | 4 |
DOIs | |
Publication status | Published - Oct 2018 |
Externally published | Yes |