Interactive scene segmentation for efficient human-in-the-loop robot manipulation
D. J. Butler, S. Elliot, and M. Cakmak, “Interactive scene segmentation for efficient human-in-the-loop robot manipulation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017, pp. 2572–2579, doi: 10.1109/IROS.2017.8206079.
Abstract
While there has been tremendous progress in autonomous robot manipulation, environments with clutter and unknown objects remain challenging particularly for the perception algorithms that support manipulation. This paper adopts a human-aided perception paradigm and investigates alternative interactive segmentation methods to allow users to segment a target object or object part. Through a first user study (N=24) we compare four interactive segmentation methods and characterize the tradeoff between efficiency and accuracy. Next we develop a hybrid segmentation interface and integrate it into an end-to-end human-in-the-loop manipulation system. In a second user study (N=12) we compare the performance of this system to a direct gripper-control system that allows similar manipulation tasks to be performed in challenging scenes. We find that this system enables more efficient manipulation with a lower mental load on the user, while offering a similar task success rate.
BibTeX Entry
@inproceedings{butler2017iros,
title = {Interactive scene segmentation for efficient human-in-the-loop robot manipulation},
author = {Butler, Daniel J. and Elliot, Sarah and Cakmak, Maya},
year = {2017},
booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages = {2572--2579},
type = {conference},
doi = {10.1109/IROS.2017.8206079}
}