Home/People Helping Robots Helping People: Crowdsourcing for Grasping Novel Objects

People Helping Robots Helping People: Crowdsourcing for Grasping Novel Objects

Alexander Sorokin, Dmitry Berenson, Siddhartha Srinivasa and Martial Hebert
Carnegie Mellon University, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10), October, 2010

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Abstract

For successful deployment, personal robots must adapt to ever-changing indoor environments. While dealing with novel objects is a largely unsolved challenge in AI, it is easy for people. In this paper we present a framework for robot supervision through Amazon Mechanical Turk. Unlike traditional models of teleoperation, people provide semantic information about the world and subjective judgements. The robot then autonomously utilizes the additional information to enhance its capabilities. The information can be collected on demand in large volumes and at low cost. We demonstrate our approach on the task of grasping unknown objects.

BibTeX Reference
@conference{Sorokin-2010-10559,
title = {People Helping Robots Helping People: Crowdsourcing for Grasping Novel Objects},
author = {Alexander Sorokin and Dmitry Berenson and Siddhartha Srinivasa and Martial Hebert},
booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10)},
keyword = {crowdsourcing, computer vision, object modeling, grasping},
school = {Robotics Institute , Carnegie Mellon University},
month = {October},
year = {2010},
address = {Pittsburgh, PA},
}
2017-09-13T10:40:33+00:00