People helping robots helping people: Crowdsourcing for grasping novel objects
People helping robots helping people: Crowdsourcing for grasping novel objects
复制标题
人们帮助机器人帮助人类：抓取新物体的众包
DOI：
10.1109/iros.2010.5650464
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
M. Hebert
中科院分区：
文献类型：
--
作者：
A. Sorokin;D. Berenson;S. Srinivasa;M. Hebert
为了成功部署，个人机器人必须适应不断变化的室内环境。虽然处理新奇的物体在人工智能中是一个很大程度上尚未解决的挑战，但对人类来说很容易。在本文中，我们提出了一个框架，通过亚马逊机械土耳其机器人监督。与传统的遥操作模型不同，人们提供有关世界的语义信息和主观判断。然后，机器人自主地利用附加信息来增强其能力。信息可以按需大量收集，成本低。我们展示了我们的方法，掌握未知物体的任务。
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.