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 without needing any task-specific training data for novel objects. To achieve this, it first uses a category-agnostic affordance prediction algorithm to select and execute among four different grasping primitive behaviors. It then recognizes picked objects with a cross-domain image classification framework that matches observed images to product images. Since product images are readily available for a wide range of objects (e.g., from the web), the system works out-of-the-box for novel objects without requiring any additional training data. Exhaustive experimental results demonstrate that our multi-affordance grasping achieves high success rates for a wide variety of objects in clutter, and our recognition algorithm achieves high accuracy for both known and novel grasped objects. The approach was part of the MIT-Princeton Team system that took 1st place in the stowing task at the 2017 Amazon Robotics Challenge.
Andy Zeng, Shuran Song, Kuan-Ting Yu, Elliott Donlon, Francois R. Hogan, Maria Bauza, Daolin Ma, Orion Taylor, Melody Liu, Eudald Romo, Nima Fazeli, Ferran Alet, Nikhil Chavan Dafle, Rachel Holladay, Isabella Morona, Prem Qu Nair, Druck Green, Ian Taylor, Weber Liu, Thomas Funkhouser, and Alberto Rodriguez.
"Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching."
International Conference on Robotics and Automation (ICRA), May 2018.
author = "Andy Zeng and Shuran Song and Kuan-Ting Yu and Elliott Donlon and
Francois R. Hogan and Maria Bauza and Daolin Ma and Orion Taylor
and Melody Liu and Eudald Romo and Nima Fazeli and Ferran Alet
and Nikhil Chavan Dafle and Rachel Holladay and Isabella Morona
and Prem Qu Nair and Druck Green and Ian Taylor and Weber Liu
and Thomas Funkhouser and Alberto Rodriguez",
title = "Robotic Pick-and-Place of Novel Objects in Clutter with
Multi-Affordance Grasping and Cross-Domain Image Matching",
booktitle = "International Conference on Robotics and Automation (ICRA)",
year = "2018",
month = may