Name
Abstract | ||
|---|---|---|
We propose a novel method for a robot to separate and segment objects in a cluttered tabletop environment. The method leverages the fact that external object boundaries produce visible edges within an object cluster. We achieve this singulation of objects by using the robot arm to perform pushing actions specifically selected to test whether particular visible edges correspond to object boundaries. We verify the separation of objects after a push by examining the clusters formed by geometric segmentation of regions residing on the table surface. To avoid explicitly representing and tracking edges across push behaviors we aggregate over all edges in a given orientation by representing the push-history as an orientation histogram. By tracking the history of directions pushed for each object cluster we can build evidence that a cluster cannot be further separated. We present quantitative and qualitative experimental results performed in a real home environment by a mobile manipulator using input from an RGB-D camera mounted on the robot's head. We show that our pushing strategy can more reliably obtain singulation in fewer pushes than an approach, that does not explicitly reason about boundary information. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IROS.2012.6385903 | Intelligent Robots and Systems |
Keywords | Field | DocType |
edge detection,image colour analysis,image representation,image segmentation,manipulators,mobile robots,object detection,object tracking,pattern clustering,position control,robot vision,RGB-D camera input,boundary information,cluster examination,cluttered tabletop environment,edge representation,edge tracking,external object boundary,guided pushing,mobile manipulator,object cluster,object segmentation,object separation,object singulation,orientation histogram,particular visible edge,push behavior,push direction history tracking,pushing action,pushing strategy,region geometric segmentation,robot arm,robot head,table surface | Object detection,Computer vision,Robotic arm,Computer science,Segmentation,Image segmentation,Video tracking,Artificial intelligence,Robot,Mobile robot,Mobile manipulator | Conference |
ISSN | ISBN | Citations |
2153-0858 | 978-1-4673-1737-5 | 18 |
PageRank | References | Authors |
0.76 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tucker Hermans | 1 | 18 | 3.13 |
| James M. Rehg | 2 | 5259 | 474.66 |
| Aaron F. Bobick | 3 | 18 | 0.76 |